Podcasts about intelligent automation

Send me a messageIn this episode of the Sustainable Supply Chain podcast, I had a cracking chat with René Schrama, Chief Commercial Officer at Peak Technologies. We dug into the evolving landscape of supply chain automation and what it truly means to “leverage automation intelligently” today.René shared how supply chain leaders are moving beyond full-scale automation projects and instead focusing on targeted improvements that actually matter. We explored why finding even six seconds to save in a warehouse process can add up to real gains, and how the Kaizen approach remains a solid guiding principle for continuous improvement.We didn't shy away from the challenges, either. René highlighted the impact of geopolitical disruptions like tariffs and shifting trade policies, and why adapting supply chain strategies has become more critical than ever.A big takeaway for me? Automation isn't about replacing people, it's about striking the right balance between human creativity and machine precision. We also discussed the importance of designing out waste, re-harvesting resources, and why open systems, not closed silos, are key to future-proofing operations.If you're in supply chain, sustainability, or digital transformation, this one's worth a listen. Let me know your thoughts in the comments below!Listen to the full episode wherever you get your podcasts, or on my website at https://www.sustainablesupplychainpodcast.com/#SupplyChain #Sustainability #Automation #Kaizen #IntelligentAutomation #PodcastElevate your brand with the ‘Sustainable Supply Chain' podcast, the voice of supply chain sustainability.Last year, this podcast's episodes were downloaded over 113,000 times by senior supply chain executives around the world.Become a sponsor. Lead the conversation.Contact me for sponsorship opportunities and turn downloads into dialogues.Act today. Influence the future.Support the showPodcast supportersI'd like to sincerely thank this podcast's generous supporters: Alicia Farag Kieran Ognev And remember you too can Support the Podcast - it is really easy and hugely important as it will enable me to continue to create more excellent episodes like this one.Podcast Sponsorship Opportunities:If you/your organisation is interested in sponsoring this podcast - I have several options available. Let's talk!FinallyIf you have any comments/suggestions or questions for the podcast - feel free to just send me a direct message on LinkedIn, or send me a text message using this link.If you liked this show, please don't forget to rate and/or review it. It makes a big difference to help new people discover it. Thanks for listening.

In this deep-dive conversation, Isaac Heller (CEO, Trullion) and Shlomo Agishtein (Director of AI, Trullion) share how AI is reshaping the future of finance and accounting. From their origin stories to the development of Trulli, Trullion's domain-specific AI, they break down what AI agents can really do, and what's just hype. You'll learn: * How Trullion evolved AI specifically for accounting workflows * What separates Trulli from generic large language models * Real-world use cases of AI agents in daily financial operations * The future of AI in audit, compliance, and reporting * Why accountants will lead, not lose, in an AI-driven industry This episode offers finance professionals a clear-eyed look at what AI means for your role today and where it's heading next.

In this episode of Zero to CEO, I speak with Harvard serial founder Shirish Nimgaonkar about how his company, eBlissAI, is leading a new era of agentic AI through self-healing, autonomous systems. Shirish explains why today's enterprise IT systems are falling short and how eBlissAI's platform is transforming endpoint management by combining real-time analytics, predictive insights, and intelligent automation. We discuss how businesses can drastically reduce operational costs, improve user productivity, and gain a superior ROI by adopting AI that not only reacts but predicts and personalizes. With enterprise tech at a tipping point, this episode explores why now is the critical moment to embrace truly autonomous solutions.

ServiceNow, the AI platform for business transformation, and Aptiv PLC, a leading global technology company focused on making the world safer, greener, and more connected with advanced software defined solutions, has announced a strategic partnership focused on driving intelligent automation and operational resilience across telco, automotive, enterprise, and industrial sectors. Combining the strength of the ServiceNow Platform with Aptiv's virtualisation platform enabled by Wind River cloud and Linux solutions - the partnership will drive greater automation and efficiency for telco and enterprise customers, with a shared vision to transform how connectivity powers the future of mobility and industrial sectors. Aptiv has also selected ServiceNow to help scale enterprise intelligence and unlock value across its organisation. Businesses face mounting pressures navigating a dynamic global landscape, while ensuring operational efficiency and continuous improvements in customer service. The collaboration between ServiceNow and Aptiv will deliver a powerful, scalable solution that connects real time data from complex, asset heavy systems with digital enterprise processes, enabling smarter decisions, faster response times, and operational agility for customers across industries. "The AI world doesn't respect organisational boundaries. It takes innovative partnerships to deliver on the potential of intelligent systems. ServiceNow and Aptiv are creating new possibilities for how industries operate, transform, and grow through next generation platforms," said ServiceNow Chairman and CEO Bill McDermott. "Together we will deliver precision, speed, and resilience in every workflow, in every sector, around the world." "Our edge to cloud solutions are purpose built for the world's most demanding environments - where safety, security, and performance are mission critical," said Kevin Clark, Chair and Chief Executive Officer, Aptiv. "With ServiceNow, we're applying the same real time, systems level intelligence that powers next generation mobility and infrastructure to the enterprise, transforming manual processes into integrated workflows that will drive operational resilience, efficiency, and performance for our customers across industries." ServiceNow's AI powered CRM workflows that connect the full telco customer lifecycle will integrate with Aptiv solutions including the Wind River Cloud Platform, a cloud native, on premises, private cloud solution, and Wind River eLxr Pro, an enterprise Linux offering for AI and mission critical workloads. Through the integration, customers are able to manage their assets through a cloud computing approach rather than traditional software. The collaboration is designed to support: Real time insights: Secure, low latency cloud deployments to ensure faster decision making and greater agility. End to end connectivity: Transforms cumbersome, manual processes into streamlined, automated workflows to enable greater connectivity and efficiency across the entire value chain. Security and scalability: Delivers robust data orchestration and management tools to handle complex workloads while ensuring regulatory compliance. The integration of ServiceNow CRM capabilities with Aptiv's platforms and technology from Wind River will enable customers to manage their own infrastructure with greater control, security, and reliability. New capabilities for virtualising and managing network functions will empower customers to achieve increased agility, flexibility, and cost effectiveness. Across industries, demand is rising for real time, intelligent systems that are secure, scalable, and reliable. Aptiv's platform powers mission critical applications from the edge to the cloud, enabling customers to capture and act on data where it's generated in vehicles, aircraft, factories, and networks. The collaboration will bring together Aptiv's edge intelligence and real time systems with ServiceNow's enterprise automation and AI ...

Claire chatted to Jeremy Hadall from the Satellite Applications Catapult about robotic systems for in-orbit servicing, assembly, and manufacturing. Jeremy Hadall has worked with robotics for his entire career, developing novel and innovative approaches for manufacturing and logistics industries. He's now turned his experience into the development of robots that enable those tasks in the orbital environment. Prior to joining the Satellite Applications Catapult, he served as Chief Engineer for Intelligent Automation at the Manufacturing Technology Centre for over ten years. He has previously served as a Royal Academy of Engineering Visiting Professor at Cranfield University. Join the Robot Talk community on Patreon: https://www.patreon.com/ClaireAsher

The post Status Go: Ep. 249 – The Rise of Intelligent Automation: From RPA to Gen AI | Peter Xu appeared first on InterVision Systems.

NVIDIA #GTC25 將於 3/17 – 21 日盛大登場，立即免費報名在線上與全球開發者一起共襄盛舉

Bio   Bala has rich experience in retail technology and process transformation. Most recently, he worked as a Principal Architect for Intelligent Automation, Innovation & Supply Chain in a global Fortune 100 retail corporation. Currently he works for a luxury brand as Principal Architect for Intelligent Automation providing technology advice for the responsible use of technology (Low Code, RPA, Chatbots, and AI). He is passionate about technology and spends his free time reading, writing technical blogs and co-chairing a special interest group with The OR Society.   Interview Highlights 02:00 Mentors and peers 04:00 Community bus 07:10 Defining AI 08:20 Contextual awareness 11:45 GenAI 14:30 The human loop 17:30 Natural Language Processing 20:45 Sentiment analysis 24:00 Implementing AI solutions 26:30 Ethics and AI 27:30 Biased algorithms 32:00 EU AI Act  33:00 Responsible use of technology   Connect   Bala Madhusoodhanan on LinkedIn     Books and references   ·       https://nymag.com/intelligencer/article/ai-artificial-intelligence-chatbots-emily-m-bender.html  - NLP   ·       https://www.theregister.com/2021/05/27/clearview_europe/  - Facial Technology Issue   ·       https://www.designnews.com/electronics-test/apple-card-most-high-profile-case-ai-bias-yet  - Apple Card story   ·       https://www.ft.com/content/2d6fc319-2165-42fb-8de1-0edf1d765be3  - Data Centre growth   ·       https://www.technologyreview.com/2024/02/06/1087793/what-babies-can-teach-ai/   ·       Independent Audit of AI Systems -   ·       Home | The Alan Turing Institute   ·       Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World, Marco Iansiti & Karim R. Lakhani   ·       AI Superpowers: China, Silicon Valley, and the New World, Kai-Fu Lee   ·       The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You, Mike Walsh   ·       Human+Machine: Reimagining Work in the Age of AI, Paul R Daugherty, H. James Wilson   ·       Superintelligence: Paths, Dangers, Strategies, Nick Bostrom   ·       The Alignment Problem: How Can Artificial Intelligence Learn Human Values, Brian Christian   ·       Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI, Reid Blackman   ·       Wanted: Human-AI Translators: Artificial Intelligence Demystified, Geertrui Mieke De Ketelaere   ·       The Future of Humanity: Terraforming Mars, Interstellar Travel, Immortality, and Our Destiny Beyond, Michio Kaku, Feodor Chin et al  Episode Transcript Intro: Hello and welcome to the Agile Innovation Leaders podcast. I'm Ula Ojiaku. On this podcast I speak with world-class leaders and doers about themselves and a variety of topics spanning Agile, Lean Innovation, Business, Leadership and much more – with actionable takeaways for you the listener. Ula Ojiaku So I have with me here, Bala Madhusoodhanan, who is a principal architect with a global luxury brand, and he looks after their RPA and AI transformation. So it's a pleasure to have you on the Agile Innovation Leaders podcast, Bala, thank you for making the time. Bala Madhusoodhanan It's a pleasure to have a conversation with the podcast and the podcast audience, Ula. I follow the podcast and there have been fantastic speakers in the past. So I feel privileged to join you on this conversation. Ula Ojiaku Well, the privilege is mine. So could you start off with telling us about yourself Bala, what have been the key points or the highlights of your life that have led to you being the Bala we know now? Bala Madhusoodhanan It's putting self into uncharted territory. So my background is mechanical engineering, and when I got the job, it was either you go into the mechanical engineering manufacturing side or the software side, which was slightly booming at that point of time, and obviously it was paying more then decided to take the software route, but eventually somewhere the path kind of overlapped. So from a mainframe background, started working on supply chain, and then came back to optimisation, tied back to manufacturing industry. Somewhere there is an overlap, but yeah, that was the first decision that probably got me here. The second decision was to work in a UK geography, rather than a US geography, which is again very strange in a lot of my peers. They generally go to Silicon Valley or East Coast, but I just took a choice to stay here for personal reasons. And then the third was like the mindset. I mean, I had over the last 15, 20 years, I had really good mentors, really good peers, so I always had their help to soundboard my crazy ideas, and I always try to keep a relationship ongoing. Ula Ojiaku What I'm hearing is, based on what you said, lots of relationships have been key to getting you to where you are today, both from mentors, peers. Could you expand on that? In what way? Bala Madhusoodhanan The technology is changing quite a lot, at least in the last 10 years. So if you look into pre-2010, there was no machine learning or it was statistics. People were just saying everything is statistics and accessibility to information was not that much, but post 2010, 2011, people started getting accessibility. Then there was a data buzz, big data came in, so there were a lot of opportunities where I could have taken a different career path, but every time I was in a dilemma which route to take, I had someone with whom either I have worked or who was my team lead or manager to guide me to tell me, like, take emotion out of the decision making and think in a calm mind, because you might jump into something and you might like it, you might not like it, you should not regret it. So again, over the course of so many such decisions, my cognitive mind has also started thinking about it. So those conversations really help. And again, collective experience. If you look into the decision making, it's not just my decision, I'm going through conversations that I had with people where they have applied their experience, so it's not just me or just not one situation, and to understand the why behind that, and that actually helps. In short, it's like a collection of conversations that I had with peers. A few of them are visionary leaders, they are good readers. So they always had a good insight on where I should focus, where I shouldn't focus, and of late recently, there has been a community bus. So a lot of things are moving to open source, there is a lot of community exchange of conversation, the blogging has picked up a lot. So, connecting to those parts also gives you a different dimension to think about. Ula Ojiaku So you said community bus, some of the listeners or people who are watching the video might not understand what you mean by the community bus. Are you talking about like meetups or communities that come around to discuss shared interests? Bala Madhusoodhanan If you are very much specifically interested in AI, or you are specifically interested in, power platform or a low code platform, there are a lot of content creators on those topics. You can go to YouTube, LinkedIn, and you get a lot of information about what's happening. They do a lot of hackathons, again, you need to invest time in all these things. If you don't, then you are basically missing the boat, but there are various channels like hackathon or meetup groups, or, I mean, it could be us like a virtual conversation like you and me, we both have some passionate topics, that's why we resonate and we are talking about it. So it's all about you taking an initiative, you finding time for it, and then you have tons and tons of information available through community or through conferences or through meetup groups. Ula Ojiaku Thanks for clarifying. So, you said as well, you had a collection of conversations that helped you whenever you were at a crossroad, some new technology or something emerges or there's a decision you had to make and checking in with your mentors, your peers and your personal Board of Directors almost, that they give you guidance. Now, looking back, would you say there were some turns you took that knowing what you know now, you would have done differently? Bala Madhusoodhanan I would have liked to study more. That is the only thing, because sometimes the educational degree, even though without a practical knowledge has a bigger advantage in certain conversation, otherwise your experience and your content should speak for you and it takes a little bit of effort and time to get that trust among leaders or peers just to, even them to trust saying like, okay, this person knows what he's talking about. I should probably trust rather than, someone has done a PhD and it's just finding the right balance of when I should have invested time in continuing my education, if I had time, I would have gone back two years and did everything that I had done, like minus two years off-set it by two years earlier. It would have given me different pathways. That is what I would think, but again, it's all constraints. I did the best at that point in time with whatever constraints I had. So I don't have any regret per se, but yeah, if there is a magic wand, I would do that. Ula Ojiaku So you are a LinkedIn top voice from AI. How would you define AI, artificial intelligence? Bala Madhusoodhanan I am a bit reluctant to give a term Artificial Intelligence. It's in my mind, it is Artificial Narrow Intelligence, it's slightly different. So let me start with a building block, which is machine learning. So machine learning is like a data labeller. You go to a Tesco store, you read the label, you know it is a can of soup because you have read the label, your brain is not only processing that image, it understands the surrounding. It does a lot of things when you pick that can of soup. You can't expect that by just feeding one model to a robot. So that's why I'm saying like it's AI is a bit over glorified in my mind. It is artificial narrow intelligence. What you do to automate certain specific tasks using a data set which is legal, ethical, and drives business value is what I would call machine learning, but yeah, it's just overhyped and heavily utilised term AI. Ula Ojiaku You said, there's a hype around artificial intelligence. So what do you mean by that? And where do you see it going? Bala Madhusoodhanan Going back to the machine learning definition that I said, it's basically predicting an output based on some input. That's as simple as what we would say machine learning. The word algorithm is basically something like a pattern finder. What you're doing is you are giving a lot of data, which is properly labelled, which has proper diversity of information, and there are multiple algorithms that can find patterns. The cleverness or engineering mind that you bring in is to select which pattern or which algorithm you would like to do for your use case. Now you're channelling the whole machine learning into one use case. That's why I'm going with the term narrow intelligence. Computers can do brilliant jobs. So you ask computers to do like a Rubik's cubes solving. It will do it very quickly because the task is very simple and it is just doing a lot of calculation. You give a Rubik's cube to a kid. It has to apply it. The brain is not trained enough, so it has to cognitively learn. Maybe it will be faster. So anything which is just pure calculation, pure computing, if the data is labelled properly, you want to predict an outcome, yes, you can use computers. One of the interesting videos that I showed in one of my previous talks was a robot trying to walk across the street. This is in 2018 or 19. The first video was basically talking about a robot crossing a street and there were vehicles coming across and the robot just had a headbutt and it just fell off. Now a four year old kid was asked to walk and it knew that I have to press a red signal. So it went to the signal stop. It knew, or the baby knew that I can only walk when it is green. And then it looks around and then walks so you can see the difference – a four year old kid has a contextual awareness of what is happening, whereas the robot, which is supposed to be called as artificial intelligence couldn't see that. So again, if you look, our human brains have been evolved over millions of years. There are like 10 billion neurons or something, and it is highly optimised. So when I sleep, there are different set of neurons which are running. When I speak to you, my eyes and ears are running, my motion sensor neurons are running, but these are all highly optimised. So the mother control knows how much energy should be sent on which neuron, right, whereas all these large language models, there is only one task. You ask it, it's just going to do that. It doesn't have that intelligence to optimise. When I sleep, maybe 90 percent of my neurons are sleeping. It's getting recharged. Only the dream neurons are working. Whereas once you put a model live, it doesn't matter, all the hundred thousand neurons would run. So, yeah, it's in very infancy state, maybe with quantum computing, maybe with more power and better chips things might change, but I don't see that happening in the next five to 10 years. Ula Ojiaku Now, what do you say about Gen AI? Would you also classify generative AI as purely artificial neural intelligence? Bala Madhusoodhanan The thing with generative AI is you're trying to generalise a lot of use cases, say ChatGPT, you can throw in a PDF, you can ask something, or you can say, hey, can you create a content for my blog or things like that, right? Again, all it is trying to do is it has some historical content with which it is trying to come up with a response. So the thing that I would say is humans are really good with creativity. If a problem is thrown at a person, he will find creative ways to solve it. The tool with which we are going to solve might be a GenAI tool, I don't know, because I don't know the problem, but because GenAI is in a hype cycle, every problem doesn't need GenAI, that's my view. So there was an interesting research which was done by someone in Montreal University. It talks about 10 of the basic tasks like converting text to text or text to speech and with a generative AI model or multiple models, because you have a lot of vendors providing different GenAI models, and then they went with task specific models and the thing that they found was the task specific models were cheap to run, very, very scalable and robust and highly accurate, right. Whereas GenAI, if, when you try to use it and when it goes into a production ready or enterprise ready and if it is used by customers or third party, which are not part of your ecosystem, you are putting yourself in some kind of risk category. There could be a risk of copyright issues. There could be a risk of IP issues. There could be risk of not getting the right consent from someone. I can say, can you create an image of a podcaster named Ula? You never know because you don't remember that one of your photos on Google or Twitter or somewhere is not set as private. No one has come and asked you saying, I'm using this image. And yeah, it's finding the right balance. So even before taking the technology, I think people should think about what problem are they trying to solve? In my mind, AI or artificial intelligence, or narrow intelligence can have two buckets, right. The first bucket is to do with how can I optimise the existing process? Like there are a lot of things that I'm doing, is there a better way to do it? Is there an efficient way to do it? Can I save time? Can I save money? Stuff like that. So that is an optimisation or driving efficiency lever. Other one could be, I know what to do. I have a lot of data, but I don't have infrastructure or people to do it, like workforce augmentation. Say, I have 10 data entry persons who are graduate level. Their only job is to review the receipts or invoices. I work in FCA. I have to manually look at it, approve it, and file it, right? Now it is a very tedious job. So all you are doing is you are augmenting the whole process with an OCR engine. So OCR is Optical Character Recognition. So there are models, which again, it's a beautiful term for what our eyes do. When we travel somewhere, we get an invoice, we exactly know where to look, right? What is the total amount? What is the currency I have paid? Have they taken the correct credit card? Is my address right? All those things, unconsciously, your brain does it. Whereas our models given by different software vendors, which have trained to capture these specific entities which are universal language, to just pass, on data set, you just pass the image on it. It just picks and maps that information. Someone else will do that job. But as part of your process design, what you would do is I will do the heavy lifting of identifying the points. And I'll give it to someone because I want someone to validate it. It's human at the end. Someone is approving it. So they basically put a human in loop and, human centric design to a problem solving situation. That's your efficiency lever, right? Then you have something called innovation level - I need to do something radical, I have not done this product or service. Yeah, that's a space where you can use AI, again, to do small proof of concepts. One example could be, I'm opening a new store, it's in a new country, I don't know how the store layout should look like. These are my products. This is the store square footage. Can you recommend me the best way so that I can sell through a lot? Now, a visual merchandising team will have some ideas on where the things should be, they might give that prompt. Those texts can be converted into image. Once you get the base image, then it's human. It's us. So it will be a starting point rather than someone implementing everything. It could be a starting point. But can you trust it? I don't know. Ula Ojiaku And that's why you said the importance of having a human in the loop. Bala Madhusoodhanan Yeah. So the human loop again, it's because we humans bring contextual awareness to the situation, which machine doesn't know. So I'll tie back this to the NLP. So Natural Language Processing, it has two components, so you have natural language understanding and then you have natural language generation. When you create a machine learning model, all it is doing is, it is understanding the structure of language. It's called form. I'm giving you 10,000 PDFs, or you're reading a Harry Potter book. There is a difference between you reading a Harry Potter book and the machine interpreting that Harry Potter book. You would have imagination. You will have context of, oh, in the last chapter, we were in the hilly region or in a valley, I think it will be like this, the words like mist, cold, wood. You started already forming images and visualising stuff. The machine doesn't do that. Machine works on this is the word, this is a pronoun, this is the noun, this is the structure of language, so the next one should be this, right? So, coming back to the natural language understanding, that is where the context and the form comes into play. Just think of some alphabets put in front of you. You have no idea, but these are the alphabet. You recognise A, you recognise B, you recognise the word, but you don't understand the context. One example is I'm swimming against the current. Now, current here is the motion of water, right? My current code base is version 01. I'm using the same current, right? The context is different. So interpreting the structure of language is one thing. So, in natural language understanding, what we try to do is we try to understand the context. NLG, Natural Language Generation, is basically how can I respond in a way where I'm giving you an answer to your query. And this combined is NLP. It's a big field, there was a research done, the professor is Emily Bender, and she one of the leading professors in the NLP space. So the experiment was very funny. It was about a parrot in an island talking to someone, and there was a shark in between, or some sea creature, which basically broke the connection and was listening to what this person was saying and mimicking. Again, this is the problem with NLP, right? You don't have understanding of the context. You don't put empathy to it. You don't understand the voice modulation. Like when I'm talking to you, you can judge what my emotion cues are, you can put empathy, you can tailor the conversation. If I'm feeling sad, you can put a different spin, whereas if I'm chatting to a robot, it's just going to give a standard response. So again, you have to be very careful in which situation you're going to use it, whether it is for a small team, whether it is going to be in public, stuff like that. Ula Ojiaku So that's interesting because sometimes I join the Masters of Scale strategy sessions and at the last one there was someone whose organisational startup was featured and apparently what their startup is doing is to build AI solutions that are able to do sentiment analysis. And I think some of these, again, in their early stages, but some of these things are already available to try to understand the tone of voice, the words they say, and match it with maybe the expression and actually can transcribe virtual meetings and say, okay, this person said this, they looked perplexed or they looked slightly happy. So what do you think about that? I understand you're saying that machines can't do that, but it seems like there are already organisations trying to push the envelope towards that direction. Bala Madhusoodhanan So the example that you gave, sentiment of the conversation, again, it is going by the structure or the words that I'm using. I am feeling good. So good, here is positive sentiment. Again, for me the capability is slightly overhyped, the reason being is it might do 20 percent or 30 percent of what a human might do, but the human is any day better than that particular use case, right? So the sentiment analysis typically works on the sentiment data set, which would say, these are the certain proverbs, these are the certain types of words, this generally referred to positive sentiment or a good sentiment or feel good factor, but the model is only good as good as the data is, right? So no one is going and constantly updating that dictionary. No one is thinking about it, like Gen Z have a different lingo, millennials had a different lingo. So, again, you have to treat it use case by use case, Ula. Ula Ojiaku At the end of the day, the way things currently are is that machines aren't at the place where they are as good as humans. Humans are still good at doing what humans do, and that's the key thing. Bala Madhusoodhanan Interesting use case that I recently read probably after COVID was immersive reading. So people with dyslexia. So again, AI is used for good as well, I'm not saying it is completely bad. So AI is used for good, like, teaching kids who are dyslexic, right? Speech to text can talk, or can translate a paragraph, the kid can hear it, and on the screen, I think one note has an immersive reader, it actually highlights which word it is, uttering into the ears and research study showed that kids who were part of the study group with this immersive reading audio textbook, they had a better grasp of the context and they performed well and they were able to manage dyslexia better. Now, again, we are using the technology, but again, kudos to the research team, they identified a real problem, they formulated how the problem could be solved, they were successful. So, again, technology is being used again. Cancer research, they invest heavily, in image clustering, brain tumours, I mean, there are a lot of use cases where it's used for good, but then again, when you're using it, you just need to think about biases. You need to understand the risk, I mean, everything is risk and reward. If your reward is out-paying the minimum risk that you're taking, then it's acceptable. Ula Ojiaku What would you advise leaders of organisations who are considering implementing AI solutions? What are the things we need to consider? Bala Madhusoodhanan Okay. So going back to the business strategy and growth. So that is something that the enterprises or big organisations would have in mind. Always have your AI goals aligned to what they want. So as I said, there are two buckets. One is your efficiency driver, operational efficiency bucket. The other one is your innovation bucket. Just have a sense check of where the business wants to invest in. Just because AI is there doesn't mean you have to use it right. Look into opportunities where you can drive more values. So that would be my first line of thought. The second would be more to do with educating leaders about AI literacy, like what each models are, what do they do? What are the pitfalls, the ethical awareness about use of AI, data privacy is big. So again, that education is just like high level, with some examples on the same business domain where it has been successful, where it has been not so successful, what are the challenges that they face? That's something that I would urge everyone to invest time in. I think I did mention about security again, over the years, the practice has been security is always kept as last. So again, I was fortunate enough to work in organisations where security first mindset was put in place, because once you have a proof of value, once you show that to people, people get excited, and it's about messaging it and making sure it is very secured, protecting the end users. So the third one would be talking about having secure first design policies or principles. Machine learning or AI is of no good if your data quality is not there. So have a data strategy is something that I would definitely recommend. Start small. I mean, just like agile, you take a value, you start small, you realise whether your hypothesis was correct or not, you monitor how you performed and then you think about scale just by hello world doesn't mean that you have mastered that. So have that mindset, start small, monitor, have constant feedback, and then you think about scaling. Ula Ojiaku What are the key things about ethics and AI, do you think leaders should be aware of at this point in time? Bala Madhusoodhanan So again, ethical is very subjective. So it's about having different stakeholders to give their honest opinion of whether your solution is the right thing to do against the value of the enterprise. And it's not your view or my view, it's a consent view and certain things where people are involved, you might need to get HR, you might need to get legal, you might need to get brand reputation team to come and assist you because you don't understand the why behind certain policies were put in place. So one is, is the solution or is the AI ethical to the core value of the enterprise? So that's the first sense check that you need to do. If you pass that sense check, then comes about a lot of other threats, I would say like, is the model that I'm using, did it have a fair representation of all data set? There's a classic case study on one of a big cloud computing giant using an AI algorithm to filter resumes and they had to stop it immediately because the data set was all Ivy League, male, white, dominant, it didn't have the right representation. Over the 10 years, if I'm just hiring certain type of people, my data is inherently biased, no matter how good my algorithm is, if I don't have that data set. The other example is clarify AI. They got into trouble on using very biased data to give an outcome on some decision making to immigration, which has a bigger ramification. Then you talk about fairness, whether the AI system is fair to give you an output. So there was a funny story about a man and a woman in California living together, and I think the woman wasn't provided a credit card, even though everything, the postcode is the same, both of them work in the same company, and it was, I think it has to do with Apple Pay. Apple Pay wanted to bring in a silver credit card, Apple card or whatever it is, but then it is so unfair that the women who was equally qualified was not given the right credit limit, and the bank clearly said the algorithm said so. Then you have privacy concern, right? So all these generic models that you have that is available, even ChatGPT for that matter. Now you can chat with ChatGPT multiple times. You can talk about someone like Trevor Noah and you can say hey, can you create a joke? Now it has been trained with the jokes that he has done, it might be available publicly. But has the creator of model got a consent saying, hey Trevor, I'm going to use your content so that I can give better, and how many such consent, even Wikipedia, if you look into Wikipedia, about 80 percent of the information is public, but it is not diversified. What I mean by that is you can search for a lot of information. If the person is from America or from UK or from Europe, maybe from India to some extent, but what is the quality of data, if you think about countries in Africa, what do you think about South America? I mean, it is not representing the total diversity of data, and we have this large language model, which has been just trained on that data, right? So there is a bias and because of that bias, your outcome might not be fair. So these two are the main things, and of course the privacy concern. So if someone goes and says, hey, you have used my data, you didn't even ask me, then you're into lawsuit. Without getting a proper consent, again, it's a bad world, it's very fast moving and people don't even, including me, I don't even read every terms and condition, I just scroll down, tick, confirm, but those things are the things where I think education should come into play. Think about it, because people don't understand what could go wrong, not to them, but someone like them. Then there is a big fear of job displacement, like if I put this AI system, what will I do with my workforce? Say I had ten people, you need to think about, you need to reimagine your workplace. These are the ten jobs my ten people are doing. If I augment six of those jobs, how can I use my ten resources effectively to do something different or that piece of puzzle is always, again, it goes back to the core values of the company, what they think about their people, how everything is back, but it's just that needs a lot of inputs from multiple stakeholders. Ula Ojiaku It ties back to the enterprise strategy, there is the values, but with technology as it has evolved over the years, things will be made obsolete, but there are new opportunities that are created, so moving from when people travelled with horses and buggies and then the automotive came up. Yes, there wasn't as much demand for horseshoes and horses and buggies, but there was a new industry, the people who would mechanics or garages and things like that. So I think it's really about that. Like, going back to what you're saying, how can you redeploy people? And that might involve, again, training, reskilling, and investing in education of the workforce so that they're able to harness AI and to do those creative things that you've emphasised over this conversation about human beings, that creative aspect, that ability to understand context and nuance and apply it to the situation. Bala Madhusoodhanan So I was fortunate to work with ForHumanity, an NGO which basically is trying to certify people to look into auditing AI systems. So EU AI Act is now in place, it will be enforced soon. So you need people to have controls on all these AI systems to protect - it's done to protect people, it's done to protect the enterprise. So I was fortunate enough to be part of that community. I'm still working closely with the Operation Research Society. Again, you should be passionate enough, you should find time to do it, and if you do it, then the universe will find a way to give you something interesting to work with. And our society, The Alan Turing Institute, the ForHumanity Society, I had a few ICO workshops, which was quite interesting because when you hear perspectives from people from different facets of life, like lawyers and solicitors, you would think, ah, this statement, I wouldn't interpret in this way. It was a good learning experience and I'm sure if I have time, I would still continue to do that and invest time in ethical AI. As technology, it's not only AI, it's ethical use of technology, so sustainability is also part of ethical bucket if you look into it. So there was an interesting paper it talks about how many data centres have been opened between 2018 to 2024, which is like six years and the power consumption has gone from X to three times X or two times X, so we have opened a lot. We have already caused damage to the environment with all these technology, and just because the technology is there, it doesn't mean you have to use it, but again, it's that educational bit, what is the right thing to do? And even the ESG awareness, people are not aware. Like now, if you go to the current TikTok trenders, they know I need to look into certified B Corp when I am buying something. The reason is because they know, and they're more passionate about saving the world. Maybe we are not, I don't know, but again, once you start educating and, telling those stories, humans are really good, so you will have a change of heart. Ula Ojiaku What I'm hearing you say is that education is key to help us to make informed choices. There is a time and place where you would need to use AI, but not everything requires it, and if we're more thoughtful in how we approach, these, because these are tools at the end of the day, then we can at least try to be more balanced in the risks and taking advantage of opportunities versus the risks around it and the impact these decisions and the tools that we choose to use make on the environment. Now, what books have you found yourself recommending most to people, and why? Bala Madhusoodhanan Because we have been talking on AI, AI Superpower is one book which was written by Kai-Fu Lee. There is this book by Brian Christian, The Alignment Problem: Machine Learning and Human Values alignment of human values and machine it was basically talking about what are the human values? Where do you want to use machine learning? How do you basically come up with a decision making, that's a really interesting read. Then there is a book called Ethical Machines by Reid Blackman. So it talks about all the ethical facets of AI, like biases, fairnesses, like data privacy, transparency, explainability, and he gives quite a detail, example and walkthrough of what that means. Another interesting book was Wanted: Human-AI Translators: Artificial Intelligence Demystified by a Dutch professor, again, really, really lovely narration of what algorithms are, what AI is, where, and all you should think about, what controls and stuff like that. So that is an interesting book. Harvard Professor Kahrim Lakhani, he wrote something called, Competing in the Age of AI, that's a good book. The Algorithmic Leader: How to Be Smart When Machines Are Smarter Than You by Mike Walsh is another good book, which I finished a couple of months back. Ula Ojiaku And if the audience wants to find you, how can they reach out to you? Bala Madhusoodhanan They can always reach out to me at LinkedIn, I would be happy to touch base through LinkedIn. Ula Ojiaku Awesome. And do you have any final words and or ask of the audience? Bala Madhusoodhanan The final word is, again, responsible use of technology. Think about not just the use case, think about the environmental impact, think about the future generation, because I think the damage is already done. So, at least not in this lifetime, maybe three or four lifetimes down the line, it might not be the beautiful earth that we have. Ula Ojiaku It's been a pleasure, as always, speaking with you, Bala, and thank you so much for sharing your insights and wisdom, and thank you for being a guest on the Agile Innovation Leaders Podcast. Bala Madhusoodhanan Thank you, lovely conversation, and yeah, looking forward to connecting with more like minded LinkedIn colleagues. Ula Ojiaku That's all we have for now. Thanks for listening. If you liked this show, do subscribe at www.agileinnovationleaders.com or your favourite podcast provider. Also share with friends and do leave a review on iTunes. This would help others find this show. I'd also love to hear from you, so please drop me an email at ula@agileinnovationleaders.com Take care and God bless!   

Robotic process automation has evolved into intelligent automation, transforming healthcare workflows. Discover how AI-powered document capture simplifies operations, boosts accuracy, and empowers teams to focus on what matters most.

Intelligent automation is transforming industries by tackling messy, unstructured workflows that traditional Robotic Process Automation (RPA) couldn't handle. In this episode, a16z partner Kimberly Tan discusses the shift from rigid RPA systems to AI-powered agents and why this evolution unlocks massive opportunities in legacy markets.Drawing on her article "RIP to RPA: The Rise of Intelligent Automation," Kimberly shares real-world examples of companies revolutionizing referral management, and highlights how startups can build impactful solutions in this space.Resources:Find Kimberly on X: https://x.com/kimberlywtanRead Kimberly's article: https://a16z.com/rip-to-rpa-the-rise-of-intelligent-automation/Stay Updated: Let us know what you think: https://ratethispodcast.com/a16zFind a16z on Twitter: https://twitter.com/a16zFind a16z on LinkedIn: https://www.linkedin.com/company/a16zSubscribe on your favorite podcast app: https://a16z.simplecast.com/Follow our host: https://twitter.com/stephsmithioPlease note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures.

In this Respiratory edition of the Industry Matters podcast, Boone Lockard, VP of Respiratory. chats with Trey Holterman, Co-Founder and CEO of Tennr, and Trevor Danley, Executive VP of Operations at Total Medical Supply. They delve into the transformative journey of Tennr, a cutting-edge intelligent automation platform. Tune in to hear about their innovative solutions, the evolution of their partnership, and the exciting advancements on the horizon for Tennr and the healthcare industry.

Send us a textIn this episode, Marcus is joined for a compelling conversation by Joan Perez-Péricot, the visionary VP and GM of HP's Industrial Print Software and Solutions. With over three decades at HP, Joan offers an insider's perspective on the seismic shifts reshaping printing. We discuss the industry's pivot towards intelligent automation and software solutions amidst global supply chain hurdles and soaring labour costs. Joan's insights into the transition from analogue to digital printing, fueled by e-commerce and web-to-print advancements, provide a insightful look at how the print landscape is evolving.Discover how AI is already revolutionising the print sector, transforming roles and redefining business strategies. Through strategic partnerships with other global tech giants such as Amazon and Microsoft, HP is poised to create unique AI applications that empower smaller businesses to thrive in a competitive market. We explore how AI enhances decision-making, automates workflows, and improves data visibility, offering transformative insights that heighten production efficiency and solve operational challenges. Joan shares how HP leverages AI resources to develop solutions that not only optimise processes but also drive a strategic shift in the print industry.BiographyAs the VP of Industrial Print Software & Solutions, Joan is responsible to expand HP's business into SaaS models, drive the Artificial Intelligence strategy and develop the next generation of PrintOS solutions portfolio.Joan is also VP Industrial Print Strategy and Sustainability, responsible of defining the vision, strategy, and transformation initiatives to accelerate growth, reduce the environmental footprint and increase the overall Industrial Print business growth and profitability.Prior to this role, Joan was the Graphics Solutions Global Head & General Manager, completing the acquisition of OFS (a workflow automation startup), developing a new SaaS business (Site Flow) and incubating new creator solutions.Before that, he was the Global Head and General Manager of the Large Format Production business, scaling-up the HP Latex business for signage and decoration, and launching the HP Stitch business for textiles digital printing.Since 1992 he has been responsible of multiple product developments, the integration of the Scitex, NUR Macroprinters & ColorSpan portfolio after being acquired by HP, and the launch of the disruptive HP Latex technology.Married with 3 kids, Joan has a degree in mechanical engineering from The School of Industrial Engineering & an MBA from ESADE business school in Barcelona. Listen on:Apple PodcastGoogle PodcastSpotifyWhat is FuturePrint? FuturePrint is a digital and in person platform and community dedicated to future print technology. Over 15,000 people per month read our articles, listen to our podcasts, view our TV features, click on our e-newsletters and attend our in-person and virtual events. We hope to see you at one of our future in-person events:FuturePrint TECH: Leaders Summit 1 April '25, Valencia, Spain FuturePrint TECH: Packaging & Labels 2-3 April '25, Valencia, SpainFuturePrint TECH: Industrial Print: 22-23 October '25, Munich, Germany

In this episode of Marketing Art and Science, CMO advisor and host Lisa Martin invites Dynatrace CMO Laura Heisman to discuss the real-world applications and impact of AI, generative AI, causal AI, and predictive analytics on the customer journey. Laura also shares her expertise in formulating marketing AI councils at companies like VMware and Dynatrace, and talks about the significant impact these councils are having on marketing-sourced business. Their discussion covers: Introduction to the CMO, her journey, and what excites her about leading marketing in the AI era. Insight into Dynatrace's marketing technology stack, the balance between creative ("art") and data-driven ("science") strategies, and how these elements are used to enhance revenue and personalization. Practical uses of AI and data in marketing at Dynatrace - its AI Council - including predictive analytics and generative AI. Exploration of how Dynatrace applies AI and data in marketing, including predictive analytics, automation, and generative AI tools like ChatGPT to differentiate and optimize marketing efforts.  

In this episode we dive into adding automation to construction work flows. The Challenge A general contractor who has brought you in to provide automations for their company. They are totally green to this. They haven't done anything to it, but the VP flew you in and said, I have seen your YouTube videos. I have to have you help us fix our company. Where do you start? Continue Learning Helena Liu's Youtube Channel Buy our new book The Critical Path Career: How to Advance in Construction Planning and Scheduling. Subscribe to the Beyond Deadlines Email Newsletter Subscribe to the ⁠⁠⁠⁠Beyond Deadlines⁠⁠⁠⁠ Linkedin Newsletter ⁠⁠Check Out Our YouTube Channel⁠⁠. Connect Follow ⁠⁠⁠Micah⁠⁠⁠, ⁠⁠⁠Greg⁠⁠⁠, and ⁠⁠Beyond Deadlines⁠⁠ on LinkedIn. Beyond Deadline It's time to raise your career to new heights with Beyond Deadlines, the ultimate destination for construction planners and schedulers. Our podcast is designed to be your go-to guide whether you're starting out in this dynamic field, transitioning from another sector, or you're a seasoned professional. Through our cutting-edge content, practical advice, and innovative tools, we help you succeed in today's fast-evolving construction planning and scheduling landscape without relying on expensive certifications and traditional educational paths. Join us on Beyond Deadlines, where we empower you to shape the future of construction planning and scheduling, making it more efficient, effective, and accessible than ever before. About Micah Micah, an Intel project leader and Google alumnus, champions next-gen planning and scheduling at both tech giants. Co-founder of Google's Computer Vision in Construction Team, he's saved projects millions via tech advancements. He writes two construction planning and scheduling newsletters and mentors the next generation of construction planners. He holds a Master of Science in Project Management, Saint Mary's University of Minnesota. About Greg Greg, an Astrophysicist turned project guru, managed £100M+ defense programs at BAE Systems (UK) and advised on international strategy. Now CEO at ⁠⁠Nodes and Links⁠⁠, he's revolutionizing projects with pioneering AI Project Controls in Construction. Experience groundbreaking strategies with Greg's expertise. Topics We Cover change management, communication, construction planning, construction, construction scheduling, creating teams, critical path method, cpm, culture, KPI, microsoft project, milestone tracking, oracle, p6, project planning, planning, planning engineer, pmp, portfolio management, predictability, presenting, primavera p6, project acceleration, project budgeting, project controls, project management, project planning, program management, resource allocation, risk management, schedule acceleration, scheduling, scope management, task sequencing, construction, construction reporting, prefabrication, preconstruction, modular construction, modularization, automation --- Support this podcast: https://podcasters.spotify.com/pod/show/beyonddeadlines/support

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Austin Reed, Co-Founder of Horizon Development, to discuss the challenges organizations face when adopting technologies like AI and machine learning, as well as the solutions.

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is sits down with Ford Kerr, Head of AI and Automation at Soar Autism Center, to discuss his journey from healthcare and his ongoing mission to infuse the organization with AI and automation tools that can enhance clinical quality and improve efficiency.

“One of the most essential parts of bringing innovation to market is often the most rarely noted,” says host Macy Donaway on the latest Resonance Test podcast. “And it's those dedicated client leads and sponsors who have political capital built that they can spend to then overcome hurdles.” We call such people mavericks, and Uma Gopinath, the CIO of Porter Airlines and our podcast guest, perfectly embodies that term. Gopinath has been a highly successful change-maker in numerous companies and industries (she was the CIO of Metrolinx, the Director of Technology and Innovation at Lush, and the AVP of Intelligent Automation at Canadian Tire Corporation). Along the way, she has learned how to thrive in the heavily male-dominated technology industry and shares some of her wisdom in this conversation. Giving back, in fact, is central to her work. “As a person of privilege, you need to share that privilege with others,” she says, noting that when at Metrolinx, she noticed the diversity of her teams was “in the low teens when we started,” and by the time she exited “We were close to 30-35% in diversity.” She says that change happens “by intention.” And notes that when a woman didn't win a particular role, she would ask her colleagues why and was often told, “But she's the second best.” To this, Gopinath argued that perhaps she was “second best because she's never been given the opportunity to be the first best.” Fixing systemic bias, she notes: “Calls for courage, calls for some unpopular statements sometimes.” Courage is a central part of Gopinath's general ethos, and it takes the shape of a willingness to be curious, to experiment (and experiment at scale: “your denominator has to be big for you to get those useful, successful experiments,” she says). Gopinath talks up the importance of focusing on the customer. Continuously. Gopinath notes that many organizations brew up a business case and do a project, “but then nobody goes back to effectively evaluate” the outcomes originally projected. Consequently, she says, “We hear lots of stories about how IT projects don't deliver.” She adds that sometimes it's “a small feedback loop that's required” and that doing “a little more to get to that bigger benefit” is something businesses need to do better. Gopinath ends with some memorable maverick-level inspiration for future leaders: “Enjoy what you're doing. If you're not having fun, then go be successful somewhere else.” Now go have fun and listen to the episode! Host: Alison Kotin Engineer: Kyp Pilalas Producer: Ken Gordon

In this episode, Amir chats with Brajesh Jha, SVP and Global Business Leader of Data Tech and AI at Genpact, about scaling Generative AI (Gen AI). They explore what 'Gen AI at scale' means, drawing parallels with past technological waves like computerization and robotic process automation. Topics include the importance of data quality, strategic and technological considerations, and reimagining business models to leverage AI effectively. Brajesh shares Genpact's transformation journey and practical advice for harnessing Gen AI's power, emphasizing a strategic, data-driven, AI-first mindset. Highlights: - 01:21 Understanding Gen AI at Scale - 02:14 Historical Context of Technological Evolution - 05:09 Challenges and Opportunities with Gen AI - 05:48 Apple Intelligence and Data Utilization - 12:10 Strategic Considerations for Gen AI - 15:23 Importance of Data Quality - 18:31 Steps for Successful Gen AI Implementation - 23:38 Future of Gen AI in Business Guest: Brajesh Jha is a Senior Executive with over two decades of experience in professional services at multi-billion-dollar technology companies. Currently, he leads Genpact's Technology, Media, and Entertainment vertical, managing global business operations that deploy Analytics, Artificial Intelligence, and Intelligent Automation capabilities. He also drives co-innovation with various micro-segments, including studios, cable providers, publishers, entertainment companies, and advertising agencies, to build new operating models and enhance customer experiences. LinkedIn: https://www.linkedin.com/in/brajeshjha --- Thank you so much for checking out this episode of The Tech Trek. We would appreciate it if you would take a minute to rate and review us on your favorite podcast player. Want to learn more about us? Head over at https://www.elevano.com Have questions or want to cover specific topics with our future guests? Please message me at https://www.linkedin.com/in/amirbormand (Amir Bormand)

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Iris Wang, President, CEO, and Founder of the UniCloud Institute, to discuss the role of holistic AI in driving business growth and innovation. They explore holistic AI strategies, ethics, and real-life applications.

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Josh Lucas, Head of GTM Automation Solutions at Workato, to explore how AI and machine learning can benefit businesses by automating the marketing processes and integrating systems, making work more efficient.

On this episode of the Six Five On the Road, host Keith Kirkpatrick is joined by Pega's Matt Healy, Director of Product Marketing, Intelligent Automation for a conversation on how Pega's innovative approach to AI and application development is reshaping industries. Their discussion covers: The evolving role of AI in application development How Pega's Blueprint technology stands out in the market Real-world impacts of Pega's intelligent automation The future vision of AI and automation at Pega Challenges and opportunities in implementing AI solutions in businesses   #Pegaworld #Pegasystems #Pega #AI #BlueprintTechnology #appdevelopment #TheSixFiveOnTheRoad #KeithKirkpatrick #MattHealy #technology

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Frank Pica, CEO and Co-Founder of Native AI, to share the positive potential of generative AI to solve real-world problems, scale businesses, and improve customer experience.

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Ana Di Grigoli, Manager of UX Design at Amazon Prime, to explore how technologies like AI enable designers to gain valuable insights into user needs and solve their problems.

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Amit Pande, a GTM Advisor and AI Investor, to explore the role of AI augmentation for go-to-market functions like sales, marketing, and customer success.

This episode features an interview with Christina Kucek, Executive Director of Intelligent Automation at CAI. She has over 15 years of consulting experience in delivering cutting-edge implementations in Conversational AI, natural language processing, and robotics process automation. At CAI, Christina guides clients through their automation journeys while delivering innovative solutions.In this episode, Shawn and Christina discuss the impact of AI on employee experience: from onboarding to accelerating workflows to building in ethics.-------------------“Employee retention a lot of times can be impacted by their first week or two of employment. They get their machine, their access to all the systems that they need. They get their email, it's already set up. They show up on day one and they're ready to go. That impression that you make as a company on their new employee will help us retain our best talent. That reduces our cost overall for trying to recruit people and train people. That retention piece is really valuable.” – Christina Kucek-------------------Episode Timestamps:*(02:44): Rapid fire questions*(07:13): Christina breaks down CAI and her role*(15:57): How AI impacts employee experience*(28:22): How AI will affect the amount of work for employees*(36:43): The future of augmented intelligence*(45:23): What's next for Christina and CAI-------------------Links:Connect with Christina on LinkedInLearn more about CAIConnect with Shawn on LinkedInCohesion Podcast

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Jeff Dillon, Founder of EdTech Connect, to share insights on how technologies like AI and machine learning are shaping the world of higher education.

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Nabeel Siddiqui, Global Senior Director and Head of Tech and Automation at SAP, to discuss the power of AI and machine learning in scaling businesses.

On this episode, Zach has the pleasure of talking with Doug Shannon, a Global Intelligent Automation Leader and a LinkedIn Top AI Voice. Together, they explore what's happening in Generative AI today. The companies behind the biggest platforms have yet to turn a profit, but they'll continue to invest and spend exponentially. Why is that? What strategies are these AI giants using to hook users and (eventually) make money? What's going on behind the scenes? Zach and Doug answer these questions and more today on the pod. Like, Subscribe, and Follow: YouTube: https://www.youtube.com/channel/UCAIUNkXmnAPgLWnqUDpUGAQ LinkedIn: https://www.linkedin.com/company/keyhole-software Twitter: @KeyholeSoftware Find even more Keyhole content on our website (https://keyholesoftware.com/). About Doug: Doug Shannon is an accomplished IT automation professional with over 20 years of experience in advanced technology roles. He excels at implementing strategic initiatives to enhance business functionality and possesses strong collaboration skills to lead diverse teams. Doug is a thought leader in digital transformation, utilizing his expertise in enterprise robotic process automation, AI, and agile project management to drive success. He has a proven track record in building self-healing automation processes and has been recognized as one of the top 50 intelligent automation leaders globally. Doug on LinkedIn: https://www.linkedin.com/in/doug-shannon/ 

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by R. Paul Singh, Acting COO at The Modern Data Company, to share insights on how AI, machine learning, and intelligent automation can help you grow your business.

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Virginia Puccio, Founder and CEO of Fuel AI, to explore the key role of high-quality, first-party data in AI development.

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Praveen Kesani, Head of Transformation and Digitization and Technology Executive (CTO), Commercial and Corporate Banking at Wells Fargo, to discuss digital transformation and automation in the banking and financial services industry.

In this episode of the D-Suite, Gartner experts share their data, analytics and AI predictions for 2024 and beyond. In the second part of this episode, we show insights from Ericsson's head of AI and automation, Rickard Wieselfors, on the role of generative AI (GenAI) for digital transformation.The predicts featured are:00:00:54 By 2026, 75% of CDAOs who fail to make organizationwide influence and measurable impact their top priority will be assimilated into technology functions. 00:05:54 By 2026, 90% of organizations will suffer more than 10 production-impacting events annually due to insufficient GenAI skills and testing investments.00:09:33 By 2025, use of natural language as a primary data management API will be the dominant interface leading to a 100x consumption of data across the ecosystem.00:13:22 By 2025, 90% of current analytics content consumers will become content creators enabled by AI. Jorg Heizenberg is a Gartner VP Analyst in D&A CDAO Leadership and Operations. Jorg explores data and analytics (D&A) trends and best practices with a human-centric focus. His primary coverage areas are the D&A strategy and operating model; data-driven culture and behavior; D&A organizations, roles, and skills. He has a background in D&A business and technology consulting with over three decades of experience in planning, designing, and implementing D&A. His motto: D&A is about people!Ehtisham Zaidi is a Gartner VP Analyst in D&A Data Architecture and Solutions. Ehtisham focuses his research on data management architecture and solutions. His coverage areas include data fabric architectures, data mesh operating models, data engineering as a discipline, and data integration architecture and technology. His recent research focus has been around the incorporation of GenAI in data management technology to improve productivity of data resources. He believes in “making data easy” and enabling “data management for the masses.”Edgar Macari is a Gartner Director Analyst in D&A Business Analytics and Data Science. Edgar specializes in guiding organizations to democratize data and analytics (D&A), maximizing the value derived from their investments in this field. His expertise spans key areas, including D&A strategy, self-service analytics, augmented analytics, analytics and business intelligence (ABI) platforms, data literacy, and cultural change. His recent research explores the profound impacts of AI on democratizing D&A. His motto: D&A is a team sport — don't play alone!Erick Brethenoux is a Gartner Distinguished VP Analyst in D&A Artificial Intelligence. Through his research and advisory duties, Erick guides organizations on the strategic, technology and pragmatic implementation of AI techniques and next-generation decision-modeling systems. Prior to Gartner, Erick has held various executive positions building products and AI platforms. Erick has also conducted a scientific mission for the French Embassy in the U.S. while conducting his research as a Ph.D. candidate at University of Delaware within a cognitive sciences multidisciplinary program. Erick is also currently an adjunct professor at the Illinois Institute of Technology in Chicago. 00:16:53 Powering Transformation by Intelligent Automation and Al Please subscribe and share the episode with your colleagues. Thank you for listening. Gartner Podcasts are a production of Gartner, the world's leading research and advisory company. Equipping executives across the enterprise with indispensable insight, advice, and tools to achieve their mission critical priorities. You can learn more at Gartner.com. All content in Gartner Podcasts is owned by Gartner and cannot be repurposed or reproduced without Gartner's consent. Gartner is an impartial, independent analyst of business and technology. This content should not be construed as a Gartner endorsement of any enterprise's product or services. All content provided by other speakers is expressly the views of those speakers and their organizations.

Show Notes: Karen Friedenberg discusses a project she worked on to design an Intelligent Automation Center of Excellence for a Fortune 500 medical supply company. The challenge was that the organization was initially looking to leverage robotics process automation (RPA) technology to automate repetitive and manual processes. This led to the development of Intelligent Automation, also known as hyper automation. Defining the Meaning of Intelligent Automation The first step in this project was defining Intelligent Automation and defining its meaning. The client wanted to develop a center of excellence to coordinate efforts across the company to take advantage of new technology and benefits quickly and in a coordinated way. The center of excellence would serve various needs and be a resource for the organization. Karen explains that the first step was to identify the pockets within the organization where people were learning about robotics, process automation, AI, and chatbots. She then interviewed stakeholders to understand their strategic imperatives and goals, and a key understanding was to let business lead the way, not the technology. The second step focused on developing the structure of the Intelligent Automation Center of Excellence (COE), its interaction with other teams, and the roles and competencies of the COE team. The COE team would be responsible for staying on top of the evolving technologies and coordinating efforts to leverage project management and program management capabilities in a coordinated way. One of the great things about new technology is putting it in the hands of the business and users, allowing them to solve problems themselves. However, there were challenges, opportunities, and fear to address,  such as change management and fear of the business starting to do this. For example, IT was beginning to fear redundancy in many of their roles.  As a solution to these challenges, it was necessary for the COE team to identify their mission, roles, and responsibilities. The Center of Excellence Explained The Center of Excellence (COE) is a team that works to identify and prioritize automation candidates in business units. Karen talks about the knockout criteria they use to assess if a process is an automation candidate and if it can be done within existing systems. The COE then uses a box prioritization matrix to assess the impact and effort of each candidate. If it is easier and less risky, it may be a candidate for a citizen developer role. Governance is also a key aspect of the COE's role. The COE's role involves oversight and sharing best practices. They train and certify citizen developers to use new technology and processes, ensuring proper controls are in place. The SDLC (Software Development Lifecycle) is a model that aims to maintain flexibility and speed while ensuring proper controls. People submit requests through various methods, such as email, phone, or using shared systems like Leisha shared through SharePoint and Microsoft tools. The COE's role is to ensure that the process is secure and efficient, while also ensuring that the right controls are in place to prevent unauthorized changes to code. Discussion on the Design Phase of a Project Karen explains that they are still in the design phase and it has not been fully executed yet. The vision was to analyze incoming requests and determine who gets help. The team is divided into a business lead and an IT lead who would work with business analysts to assess the project's feasibility. The group provide different levels of support, such as a half-hour conversation or a three-month project with a business analyst and consultants.The first step is to train the business unit citizen developer and to provide regular reviews to the client. The team would also provide additional technical, business process, and change management assistance. The goal is to help the client team navigate their blockers and be a centralized source for sharing learnings and best practices across the business. Integration with The Center of Excellence The COE is complex and interacts with multiple systems, including  project management teams and various departments across the business. The team would also be aware of other projects in the company and work with them to ensure each project is documented and shared within the ecosystem to share information across departments and projects as required. Karen discusses the development of an Intelligent Automation center of excellence and the marketing approach taken to promote the service.  The center consists of five people and is being promoted internally through business optimization managers. The company is taking a crawl, walk, run approach, starting small and growing. She explains that some barriers to the center include resourcing, funding, and fear of AI impacting employees' jobs. Organizational change management is crucial in these efforts, as it ensures sustainability and avoids unintended consequences for employees. The Benefits of a COE The company anticipates benefits from the center of excellence, such as faster deployment of technologies, reduced manual tasks, and cohesion of information. The technology has tremendous benefits, but the bigger benefit is the new ways of working that can be applied across various parts of the business. The center of excellence also helps in teaching new ways of working and chain collaboration between the business and IT. Timestamps: 01:02 Designing Intelligent Automation Center of Excellence for a Fortune 500 company 02:22 Establishing an Intelligent Automation Center of Excellence 06:40 Automation and citizen development in a business unit 10:49 Implementing a citizen developer program 14:32 Implementing an Intelligent Automation center of excellence Links Website: https://www.piconsult.net/ LinkedIn: https://www.linkedin.com/in/karen-friedenberg/ Unleashed is produced by Umbrex, which has a mission of connecting independent management consultants with one another, creating opportunities for members to meet, build relationships, and share lessons learned. Learn more at www.umbrex.com.  

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Tracy Wehringer, Founder and CMO of Moonshot-Strategy, to unveil the role of AI and machine learning in transforming data analytics and customer insights, and how the ever-evolving technology has helped her drive business growth and optimize marketing strategies.

We're thrilled to host Kence Anderson, a trailblazer at the forefront of autonomous AI in the industrial sector. Kence brings a wealth of experience from his tenure as the director of autonomous AI adoption at Microsoft to his current role as CEO of Composabl, where he's redefining the landscape of intelligent automation with a platform designed to democratize the creation of autonomous agents. With a remarkable track record of designing over 150 autonomous decision-making AI systems for large enterprises, Kence has mastered the art of bridging the gap between cutting-edge AI technology and practical industrial application.In this episode, Kence will unpack the essentials of effective collaboration between AI technologists and industrial stakeholders, share the ambitions behind his 'Introduction to Industrial AI' course, and provide a firsthand look at how autonomous AI can revolutionize industries by optimizing processes in real-time. We'll delve into the synergy of AI for Perception and Action in enhancing automation, tackle the challenges of deploying AI-powered systems, and explore the transformative potential of machine teaching. Plus, Kence will highlight the game-changing advantages of Composabl's no-code platform, making the power of AI accessible to all, regardless of their technical background.Join us as we navigate the future of industrial automation with Kence Anderson, discovering how today's AI innovations are paving the way for a smarter, more efficient world.

In this episode of How to Grow Using AI, ML, and Intelligent Automation, host Nicholas Cole is joined by Philip Madero Hammarskiöld, CRO of Trudy, to explore the potential of AI in influencer marketing. They delve into best practices in AI and influencer marketing, how AI can match the perfect influencer for your brand, and future trends of AI in influencer marketing.

In this episode of How to Grow Using AI, Machine Learning, and Intelligent Automation, host Nicholas Cole is joined by Cyril Coste, CDO of Digital and Growth, to discuss how to utilize generative AI to unlock the present and future possibilities for customer engagement.

Welcome to how to grow using A I machine learning and intelligent automation brought to you by eClerx. Join us as we dive deep into the impact of artificial intelligence and machine learning. This is what you can expect from this podcast. We will empower you with real life examples and actionable insights from the E clerks team and industry experts. Search for how to grow using A I machine learning and intelligent automation on Apple podcast, Google podcast, Spotify or your favorite podcast platform. And be sure to follow us to never miss an episode. Thank you for tuning in and let's explore the future of business growth using A I and machine market.

In this episode, David is joined by Philip Holt, who has over 30 years of experience in working with industry giants such as GKN Aerospace, Phillips, Gillette, and Travelport. He has built a reputation for being a global expert in Lean thinking, but also in lean doing and in lean being. Leading Lean by Living Lean, which is also the title of his new book Philip explains how to use Lean tools to improve the workplace and the chances of success. He does this by sharing several real-world examples. KEY TAKEAWAYS Making the workplace better for your people your business performs better. Lean is not about reducing the number of employees. You need to address people´s fear of losing their job and show them what is in it for them e.g., less need to work late. Engagement is essential, if someone feels threatened by a change, they will resist it. The tools aren´t the end game, business improvement is the end game. Lean enables you to build strategies and engage everyone in delivering them. Lean works for every kind of business and process. When introducing technology focus on the people engaging in that technology. BEST MOMENTS‘It´s about respect for people and engaging those people in making results better,' ‘Standardize the ways of working, where we know the solution.' ‘We´ve got to keep the humanity in how we deploy it (AI)' EPISODE RESOURCEShttps://uk.linkedin.com/in/philipholthttps://leadingwithlean.com/  Podcast - https://podcasts.apple.com/ro/podcast/leading-lean-by-living-lean-with-philip-holt/id1444154403?i=1000574562273 Philip Holt Books: https://www.amazon.co.uk/stores/Philip-Holt/author/B06WD2G1VB Clifton Strengths - https://www.gallup.com/cliftonstrengths/en/252137/home.aspx https://kaizen.com GUEST BIO Philip is the founder and Managing Director of Leading with Lean, a Consultancy Service which provides companies with a People-centred approach to Business Transformation. Until late 2023, he was Senior Vice President, Operational Excellence at GKN Aerospace, the world's leading multi-technology tier 1 Aerospace supplier and previously Vice President, Continuous Improvement & Intelligent Automation at Travelport, a leading Travel Commerce Platform. Prior to that he held a number of senior Lean Leadership roles within Royal Philips, most notably Head of Continuous Improvement for Philips, Head of Continuous Improvement for the Consumer Lifestyle sector, and Head of Operational Excellence, Accounting Operations. Philip was the lead author of the Philips Lean Excellence Model. Philip has over 30 years of business experience in leadership roles spanning the customer value chain, in Industry Leading Companies such as GKN Aerospace, Philips, Gillette, and Travelport. During this time he has built up an impressive reputation in Lean Leadership practices and is a regular speaker at industry conferences. He studied at Manchester Metropolitan University, Warwick Business School, and the University of Pennsylvania (Wharton School). Leading Lean by Living Lean: Changing how you lead, not who you are; is his third book, following the Axiom 2020 Business Book Awards Bronze Medal winner, The Simplicity of Lean: Defeating Complexity; Delivering Excellence and the success of Leading with Lean: An Experience-based guide to Leading a Lean Transformation. ABOUT THE SHOWPeople with purpose make a difference. Imagine a world where more people can just get their purpose out of them, into a plan and then actually make it happen. What a world that would be - People everywhere finding meaning and harnessing that to bring inspiration and energy to each and every day, changing lives for the better. But no one ever achieved anything on their own - we all have something unique to bring and that means we all have to play our part - if we want to go far, we have to go together and lead or serve towards a vision of the world we want to see. Everyone has a story to tell, and this show is where these stories come to life. ABOUT THE HOSTDavid Roberts is a highly regarded CEO, mentor, and investor with 30 years of experience across multiple sectors. As an intrapreneur and entrepreneur, David has bought, grown, started and sold several businesses, working with values-driven start-ups, award-winning SMEs, and multinational corporations on strategies for service excellence, leadership, and profitable growth. David's passion is for purpose and creating an environment where everyone can succeed, through building teams that get things done, execute on their mission with passion, deliver exceptional service and really make a difference. ARTWORK CREDITPenny Roberts - https://www.instagram.com/penpennypencils  CONTACT METHODS LinkedIn - https://www.linkedin.com/in/david-roberts-nu-heat/Facebook - https://www.facebook.com/DavidRobertsPeopleWithPurposeInstagram - https://www.instagram.com/davidcroberts_/Clubhouse - https://www.clubhouse.com/@davidcroberts?utm_medium=ch_profile&utm_campaign=MBv1ubya1-oOBXc_uQKFHw-46334

In an engaging interview with Kerry W. Kirby, the Founder and CEO of 365 Connect, we delve into the ever-changing landscape of property management through the lens of automation and artificial intelligence.Automated Leasing Platforms: Kerry Kirby introduces us to an automated lease signing platform that promises precision and ease for multifamily owners and operators. By harnessing the robust legal framework of Blue Moon's lease documents and integrating with screening services, 365 Connect is reducing the margin for error.The Fight Against Multifamily Labor Shortages: With a strategic blend of AI and automation dubbed Intelligent Automation, Kirby outlines how embracing technology can offer a stark solution to the industry's pain points regarding labor shortages and the grind of repetitive tasks while emphasizing the pivotal role of compliance in this journey.Streamline with AI:The pressing issue of bureaucratic red tape, especially in light of new regulations like the junk fee bill, cannot be overstated. With compliance at its core, 365 Connect has placed systematic guardrails to ensure operators stay within the bounds of the law without compromise.Personalization vs. Personal:An intriguing contrast highlighted by Patrick Antrim emphasizes the shifting paradigm from traditional personnel-heavy operations to a personalized, technology-driven approach. Integrating technology, he suggests, does not detract from customer experience; on the contrary, it elevates it by providing team members with tools to enhance their capabilities.Starting Small:A nod towards cautious optimism is given as Patrick suggests a parallel adoption strategy, ensuring validation at every step in favor of large-scale, untested changes.Multifamily Customer-Centric Innovation:Both Antrim and Kirby agree that any technological integration must prioritize the customer experience. It's about a delicate balance between tech and touch, where augmented human interaction remains paramount.The 365 Connect Promise:Kerry W. Kirby proudly notes 365 Connect's commitment to personalized, no-pressure service – truly a hallmark of their customer-centric ethos.Enthusiasm for 365 Connect's Technological Advances:As the conversation nears its end, Patrick Antrim applauds Kirby's forward-thinking vision in the creation of a lease signing experience that is not only seamless but a substantial addition to 365 Connect's already impressive array of technologies.Equip your multifamily operation with the expert insights and groundbreaking tools of the digital age - because at Multifamily Innovation, we believe in crafting tomorrow's living experiences today, and with Kerry W. Kirby's guidance, the path has never been clearer. Connect:Patrick Antrim: https://www.linkedin.com/in/patrickantrim/Multifamily Innovation® Council: https://multifamilyinnovation.com/council/Multifamily Innovation® Summit: https://multifamilyinnovation.com/ Multifamily Women®: https://multifamilywomen.com/

In a rapidly evolving tech landscape, stagnant and outdated business processes are more than just financial pitfalls—they are barriers to scaling and innovation. The incentives to shift to automation and leverage AI are massive. Susannah Streeter welcomes William Smith, Senior Manager for EY Consulting, Jack Virdee, VP of Finance and Automation Leader at Omnicom, and Stephen Siciliano, VP Power Automate at Microsoft, to deep dive into the world of automation and AI. EY refers to the global organization, and may refer to one or more of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. The views of third parties set out in this publication are not necessarily the views of the global EY organization or its member firms. Moreover, they should be seen in the context of the time they were made.

Shreekant Mandvikar is an Intelligent Automation expert who has helped 20+ customers on their Intelligent Automation journey. He currently leads Intelligent Automation initiatives at Ally Financial. In this chat, we discuss his Intelligent Automation journey and learnings, interesting use cases, tracking value, Gen AI, and more. More information and Links: More about Shreekant : shreekantmandvikar.com Connect with Shreekant: linkedin.com/in/shreekant-mandvikar Visit Nandan on the web at nandan.info

Learn about intelligent automation in finance and how AI and ML can improve modern financial processes. The discussion was recorded live at Workday Rising in San Francisco, between analyst Michael Krigsman and John Hugo, VP of Financial Products & Go To Market at Workday. Important highlights from the conversation include:► *Digital Transformation in Financial Processes:* Insights into how digital transformation is reshaping financial processes, helping companies navigate economic changes and evolving business models.► *Intelligent Automation and Operational Efficiency:* Examination of the impact of intelligent process automation and AI on cost management, staffing, and compliance in finance.► *Adoption of AI Process Automation:* Discussion of the cultural shift towards data-driven decision-making, emphasizing the role of automation tools in leveraging real-time data and predictive analytics.*Read the complete transcript:* https://www.cxotalk.com/episode/intelligent-automation-in-finance-with-workday*John Hugo* joined Workday, Inc. as Vice President, Financials Products and Go To Market in 2015. Prior to Workday, John was Senior Vice President & Corporate Controller, and Principal Accounting Officer, at Life Time Fitness, Inc., a Minneapolis, Minnesota based Healthy Way of Life company. Prior to Life Time Fitness, John held accounting and financial leadership roles with CompleTel Europe, N.V. (Paris, France), Jones Intercable, Inc. (Denver, Colorado), and started his career at Arthur Andersen LLP (Denver, Colorado).*Michael Krigsman* is an industry analyst and publisher of CXOTalk. For three decades, he has advised enterprise technology companies on market messaging and positioning strategy. He has written over 1,000 blogs on leadership and digital transformation and created almost 1,000 video interviews with the world's top business leaders on these topics. His work has been referenced in the media over 1,000 times and in over 50 books. He has presented and moderated panels at numerous industry events around the world.#intelligentautomation #workdayfinancetraining #enterpriseai #financialmanagement #cxotalk

More and more, companies are unraveling the transformative power of digital technologies in manufacturing. On this episode, we welcome Amit Patel, Director of Intelligent Automation at Emerson, as he dives into digital transformation, emphasizing its role in deploying tools and technologies for real-time insights and informed decision-making. Patel highlights the Floor to Cloud approach, advocating for a start-small-and-scale-fast mindset. Also, hear how energy monitoring boosts sustainability, aids skills development, and enhances productivity.PACK EXPO East returns to Philly in March 2024. It's your east coast connection for packaging and processing solutions. Be there to catch up on the latest industry advances, connect with suppliers and land on the right solutions for your entire production line—from automation and sustainability to e-commerce and much more. Register at packexpoeast.com.Support the showRegister for PACK EXPO Las Vegas today!

Dan Lucarini discusses “The Fourth Wave of Intelligent Document Processing.” Dan is an industry analyst with Deep Analysis, a boutique research group focused on AI innovation for digital transformation. Dan is the lead analyst for Intelligent Document Processing (IDP) and contributing analyst to the Intelligent Automation, ECM and Unstructured Data Management practices. Host, Kevin Craine

On this episode of DGTL Voices, Ed welcome back Dr. Aaron Neinstein to chat about his new role as Chief Medical Officer at Notable. Together they dig into AI & Automation, a healthcare superpower, that can be used to improve healthcare workflows for better care delivery. Aaron shares insights on the most valuable piece of advice he's ever received and the importance of betting on yourself. Notable is the leading intelligent automation company for healthcare. Learn more about Notable Health: https://www.notablehealth.com/ Check our Aaron's first episode of DGTL Voices: https://dgtlvoices.podbean.com/e/the-crossroads-of-marketing-dgtl-health-ft-sarah-sanders-dr-aaron-neinstein/ 

See omnystudio.com/listener for privacy information.

Intelligent automation can help combat the human biases that can lead to discriminatory hiring practices. In this episode of Smart Talks with IBM, Malcolm Gladwell takes on this topic with Jacob Goldstein, host of What's Your Problem, and guest Angela Hood, founder and CEO of ThisWay Global. They discuss how intelligent automation can accelerate inclusive hiring practices, why machines can mitigate bias but not remove it, and why diverse companies are more competitive. This is a paid advertisement from IBM.See omnystudio.com/listener for privacy information.

Intelligent automation can help combat the human biases that can lead to discriminatory hiring practices. In this episode of Smart Talks with IBM, Malcolm Gladwell takes on this topic with Jacob Goldstein, host of What's Your Problem?, and guest Angela Hood, founder and CEO of ThisWay Global. They discuss how intelligent automation can accelerate inclusive hiring practices, why machines can mitigate bias but not remove it, and why diverse companies are more competitive. This is a paid advertisement from IBM.See omnystudio.com/listener for privacy information.

Intelligent automation can help combat the human biases that can lead to discriminatory hiring practices. In this episode of Smart Talks with IBM, Malcolm Gladwell takes on this topic with Jacob Goldstein, host of What's Your Problem?, and guest Angela Hood, founder and CEO of ThisWay Global. They discuss how intelligent automation can accelerate inclusive hiring practices, why machines can mitigate bias but not remove it, and why diverse companies are more competitive. This is a paid advertisement from IBM.Support the show: https://www.steveharveyfm.com/See omnystudio.com/listener for privacy information.