Dr. Gleb Tsipursky – The Office Whisperer
Nirit Cohen – WorkFutures
Angela Howard – Culture Expert
Drew Jones – Design & Innovation
Jonathan Price – CRE & Flex Expert
About This Episode
In this compelling episode of The Future of Work® Podcast, we dive into the transformative intersection of artificial intelligence, human‑centered automation and workplace evolution. We’re joined by three industry trail‑blazers: Angela Hood, founder and CEO of ThisWay Global — a company that uses AI to mitigate bias, match talent and unlock human potential across thousands of organizations. Jeremy Fennema, a seasoned IT executive and fractional CTO, who brings over two decades of experience in digital transformation, agile innovation and applying AI inside enterprise workflows. And Ram Srinivasan, an executive consultant and AI adoption leader at JLL, MIT alumnus and author of The Conscious Machine, who explores how AI can amplify human potential rather than replace it.
Together, they unpack critical topics for the future of work — how remote/virtual and in‑office working models will co‑exist, why AI adoption is non‑negotiable for knowledge workers, how organizational practices must evolve to manage bias and human‑centered systems, what the shifting skillsets are for tomorrow’s workforce, and how companies can move beyond the hype of AI into measurable value.
From talent sourcing and diversity ROI to developers, testers and QA in an AI‑augmented world, this conversation is rich with strategic insights and practical take‑aways for leaders, technologists and everyone working at the intersection of people and technology.
About Angela Hood
Following 4 years of R&D at the University of Cambridge in England, CEO and founder Angela Hood returned to Austin, Texas to build ThisWay Global Inc., a company that converges technology with talent networks (not job boards) to unlock human potential.
Today, ThisWay is one of the fastest growing SaaS automation companies in the world, serving over 5000 company customers. ThisWay provides unbiased talent matching and sourcing through its proprietary network of over 8,500 unique, diverse community partners.
Hood is a well respected thought leader and international keynote speaker on the topics of mitigating bias using artificial intelligence, the ROI of diversity and human-centric automation.
About Jeremy Fennema
Jeremy Fennema is a seasoned IT executive with over twenty years of experience in driving technological innovation and strategic growth within the e-commerce and IT sectors. As a former Vice President and CTO, he specializes in digital transformation, agile methodologies, and operational excellence, adept at turning complex challenges into strategic opportunities at Fennema.io.
Jeremy’s career is distinguished by his ability to lead dynamic teams, manage multimillion-dollar budgets, and implement solutions that significantly enhance customer engagement and operational efficiency. Passionate about leveraging technology to advance business objectives, Jeremy now offers his expertise as a fractional CTO, partnering with organizations to foster innovation and achieve sustainable growth.
About Ram Srinivasan
Ram Srinivasan is an Executive Management Consultant and AI Adoption Leader at JLL, where he guides Fortune 500 companies through digital transformation and AI integration to shape the future of work. An MIT alumnus with over 15 certifications in AI, machine learning, and data science, Ram combines deep technological expertise with financial and governance acumen as a Chartered Accountant and Chartered Secretary.
He’s the author of The Conscious Machine and the forthcoming The Exponential Human, both exploring how AI can amplify human potential. A recognized thought leader featured in Harvard Business Review and Business Insider, Ram champions human-centered innovation, advocating for technology that aligns with organizational values and enhances human flourishing.
What You’ll Learn
- Why remote and hybrid work models are no longer optional for knowledge workers, and how companies must be transparent about their policies.
- How AI tools like code‑assistants are changing the role of developers and testers, and why quality assurance becomes more critical than ever.
- The importance of diversity, bias mitigation and human‑centered automation in AI systems.
- How generative AI (LLMs, large‑object models) is being applied as a general‑purpose technology across work, and how non‑engineers can adopt them.
- Why resisting AI adoption means the risk of being bypassed in your career or organization.
- How organizations should shift skillsets: developers become overseers of AI‑generated code; testers become guardians of security and quality.
- The myth that you must be an AI engineer to use AI, and instead how you can become a “director” of AI tools.
- How talent matching and sourcing are being transformed by AI at scale, and what that means for HR and recruiting.
- What it means to build human‑flourishing systems in the workplace of the future rather than simply automate for efficiency.
- Practical steps leaders can take now to prepare their workforce, systems and culture for the AI‑driven future of work.
Transcript
Host AI
[ 00:00:00 ]Welcome to the Future of Work podcast, where we explore what’s next in work, workplace, and the human experience. You’re listening to a Future of Work Expert Insights, a special format where we bring together the most thought-provoking insights from our top guests around a single topic shaping the future of work.
More stories for you
Host AI
[ 00:00:20 ] In this episode, the topic is tech innovation, exploring how emerging technologies are transforming the way we work, collaborate, and lead. From AI-driven decision-making and automation to digital ethics and human-centric design, our experts share insights on how innovation is reshaping productivity, creativity, and connection in the modern workplace, and what it means for the future of work.
Host AI
[ 00:00:45 ] We’ve curated conversations with three of the sharpest minds in technology innovation.
Host AI
[ 00:00:53 ] Each offering unique insights into AI, automation, and the transformative power of technology shaping the future of work. Let’s begin.
Host AI
[ 00:01:03 ] In a world where AI is evolving faster than most companies can keep up, a new kind of skill gap is emerging. And it’s not just technical. From hiring to software development to leadership itself, the human edge is being redefined. In this episode, we explore how AI is transforming the way we work and how people can stay ahead.
Host AI
[ 00:01:24 ] Our first guest is Angela Hood, CEO of This Way Global, where she’s helping over 5,000 companies match diverse talent using unbiased AI tools. Angela explores how we can use both empathy and AI to build better teams and careers in a flexible first world.
Host AI
[ 00:01:42 ] In an era where flexible work is no longer just a perk, but an expectation, how can companies balance remote first preferences with the power of in-person collaboration? And what role does transparency play in building trust across distributed teams?
Angela Hood
[ 00:01:57 ] So the remote question is a question that is, I would say, top of mind for every candidate and every company, because knowledge workers, so people that use technology on a regular basis every single day, have the flexibility to be able to use that technology in a home office, in a virtual office, if they want.
Angela Hood
[ 00:02:20 ] The capacity, though, to innovate, we know, is better when people are in a room. It doesn’t mean they have to be in a room all day, every day. But when they can get together at moments in time and all double down and stay super focused on a particular problem they want to solve. We know that those solutions happen faster and they happen because of a greater diversity of thought as well. So there’s a few components there that are all about humans. So I think first and foremost we have to recognize a lot of people, their knowledge workers, want a virtual or remote office. They do not want to have to come into the office. Okay, that’s just the way it is. I don’t see that changing, and so it’s up to businesses to figure out how do they manage that.
Angela Hood
[ 00:03:04 ] This is a big one. And be transparent with their workforce and the candidates that are coming into their company, and tell them what the policy is and try to help them understand why. But be transparent. Don’t say it’s one thing and then change it on them. So by the time I was in engineering school, we were using calculators. They were TI and Texas Instruments calculators.
Angela Hood
[ 00:03:27 ] There are people in my class that use their TI calculator better than I could, right? Like they were wizards. They were masterminds. Where did I benefit? I could explain to a customer what we were going to do as engineers, how it was going to benefit them. But I wasn’t wielding the calculator as fast as they were or even as good as they were. We have differentiation as humans. We’re going to continue to have that with the use of AI. Some people are going to adopt it and be powerhouses at it. Some are going to struggle a little bit, but I think that if you want to be successful and if you are going to be in your career for more than five years, you really need to learn how to use AI because I think you will end up getting left behind if you cannot operate AI for your own use in business. And you need to find out what you’re good at. Are you good at using a specific platform? Are you good at using it to create better documents?
Angela Hood
[ 00:04:29 ] But to resist it, I think, ends up leaving other people the ability to bypass you.
Host AI
[ 00:04:37 ] Angela reminds us that the future of work is personal, and no two people will adopt AI the same way. But what happens when AI starts helping us do our jobs directly? If Angela reminds us that AI must serve people, Jeremy takes us inside the code itself, where humans and machines are learning to work side by side. But what does collaboration look like when your teammate might just be an algorithm? Our next guest is Jeremy Fenema, a fractional CTO and former VP of engineering, now helping businesses adopt AI in practical, secure, and scalable ways. Jeremy shows us how AI is becoming a co-pilot across job functions and why trust still depends on human judgment.
Host AI
[ 00:05:19 ] As AI tools become increasingly embedded in daily workflows, from writing code to building spreadsheets, how do we rethink the role of human workers and where should we be focusing our skill development to stay relevant?
Jeremy Fennema
[ 00:05:33 ] I wonder if a lot of the tech layoffs, for instance, have been driven by this concept that if they develop AI in a more sophisticated fashion, that they won’t actually need, you know, all of these people. They needed to cut them anyway because they wanted to make their bottom line look better. But they may, in fact, be anticipating that they’re not going to bring them back because they think, you know, AI can supplant some of that. and so, right now, right currently, uh, you can have your integrated development environment your IDE) up as a developer, and there’s plugins that will sit alongside your coding and start suggesting next blocks of code for you or coding whole sections for you. You’ve got things like AWS’s CodeWhisperer. There’s a number of technologies inside of ChatGPT that you can use. I was just using one the other day to code a Flutter app completely from scratch with AI doing all of the coding and configuration for me, and it was an exceptional experience, but I think that there’s a difference between AI doing that work for you or doing that work alongside of you and saying you
Jeremy Fennema
[ 00:06:53 ] don’t need people to do that work.
Jeremy Fennema
[ 00:06:58 ] I also think it’s going to shift that skill set into testing. So one of the things that you have right now in a good SDLC process is that you distance the developers from the testing process, right? You don’t really want the developers who coded the [the] content you know coded the [the] programs to do the testing on the programs because they’ve got an implicit bias right there. Um, it’s amazing. It always works.
Jeremy Fennema
[ 00:07:27 ] But when you have a different group that’s testing it, whether it’s peer testing or just a full QA system that’s testing those, you create a better quality product because you’ve got other people that are looking at it. i think one of the things that you’ll probably see alongside of this is that the role of the developer will be to make sure that they’re testing the the ai code and and that’s something that actually is one of the big security concerns that you see out there right now if you read current articles about what’s happening with ai is there are developers that are using ai to generate code like like i did um but they’re not going back and testing it right they’re just using it they’re saying well ai generated so it must be great and then they’re not spending any time uh doing any kind of quality control on it and you can have bugs in there you Could have security vulnerabilities in there. Um, so I think you know, that’s certainly an issue.
Jeremy Fennema
[ 00:08:30 ] But I also think some of that tends to be written by people that are trying to justify keeping developers. Keeping developers in an existing development role and sort of the pushback against adopting AI wholesale. So I think it’s easy to talk about this in terms of developers, but I want to take it away from that sort of space a little bit and just, you know, bring it into maybe a little bit of a different space. Let’s think about the person working in finance who is struggling with some spreadsheets that they’re trying to figure out how to get to the point that they’re working the way that they want them to work to be able to generate data for some report that they’re trying to put together. If you think about how that gets solved today, they’re maybe reaching out to some colleagues, they’re doing some Google searches, maybe they post on a forum, they’re using a number of traditional troubleshooting methods, or they just keep hacking away at it.
Jeremy Fennema
[ 00:09:32 ] But that can take hours, it can take days, maybe even weeks to solve some of those problems. And I think one of the shifts that we’ll see is that AI is going to sit there alongside of them.
Host AI
[ 00:09:47 ] Jeremy opened the door to AI as a hands-on copilot. But how do we make sure it remains human-centered? Our next guest takes us further, inviting us to lead, not just use, the exponential intelligence now at our fingertips.
Host AI
[ 00:10:01 ] From coding to leadership, AI is becoming part of every job, yet not everyone needs to be a technologist. Our next expert believes the future belongs to those who can direct intelligence, not just build it. And he sees that shift happening right now.
Host AI
[ 00:10:18 ] Our next guest, Ram Srinivasan, is an AI adoption leader at JLL and author of The Conscious Machine, guiding Fortune 500s through AI transformation with a human-centered lens. Ram reframes AI as a creative multiplier and says your leadership, not your coding skills, will shape the future.
Host AI
[ 00:10:37 ] Many believe that using AI requires being a coder or a technologist. But what if the future of work is about directing intelligence, not just building it? How should we be approaching AI as a general purpose tool for amplifying human potential?
Ram Srinivasan
[ 00:10:52 ] There is business application of AI. There are so many different forms of AI. AI is an umbrella term. and many aspects of which already exist— things like rule-based AI, your social media feed is AI, GPS is AI, flash trading, algorithmic trading is AI, whether predictions are AI, there’s computer vision systems that are AI, self-driving cars are AI, all of those things are AI.
Ram Srinivasan
[ 00:11:15 ] What we are experiencing right now as a wave is generative AI. Things like large language models, large object models, things that create new content from training data. That’s the current wave. Um, and the second myth is kind of aligned with that where people confuse this with something very specific. It is general-purpose technology. GPT, in my view, stands for general-purpose technology, where this technology can be applied generally to multiple different aspects of work. This is not like SAS. This is not like Workday, Oracle, ERP systems, which an enterprise implements. This is more like Excel, Word, PowerPoint. That in your hands can create something very unique. Each one of us has access to those tools. We produce very unique outputs from it that probably even the makers of Microsoft did not envision. So similarly, these language models, these general purpose technologies that we have as generative AI. Output from that is in our hands and I would apply them very very generally as opposed to very specifically.
Ram Srinivasan
[ 00:12:21 ] The third myth that I see typically is this idea that you need to be an AI expert of some kind— an engineer, a coder, and you know, AI Python software engineer or something like this. It’s not that you need to be an engineer. What you need to be is a director. You have like a movie director, who has multiple different skills at disposal. You right now has have 1,000 PhDs in your pocket. If I may paraphrase a Steve Jobs quote, you have 1,000 PhDs in your pocket. The question is, how do you use them? We spoke about IQ. These models now are at an average IQ higher than 120.
Ram Srinivasan
[ 00:13:04 ] In some cases, even more than 130. That’s genius level IQ that’s higher than 98%.
Ram Srinivasan
[ 00:13:13 ] This is where we are at. So the question is, how do we use this high IQ capacity that all of us have? And if you want to really touch the future, I would say you can touch it right now. Just use these models.
Host AI
[ 00:13:27 ] As we’ve heard today, AI isn’t replacing people. It’s redefining what we’re capable of. From Angela’s call for transparency and human connection, to Jeremy’s view of AI as a trusted co-pilot, to Ram’s vision of technology as a creative amplifier, the future of work is about partnership. The real challenge now isn’t learning to use AI, it’s learning to lead with it.
Host AI
[ 00:13:51 ] Thanks for listening to this Expert Insights episode of the Future of Work podcast. If you found it insightful, share it with a colleague, leave us a review, or check out our show notes for links to each guest’s full interview. Until next time, keep asking not just where we work, but how we work better together.
Host
[ 00:14:10 ] If it’s impacting the future of work, it’s in the Future of Work podcast by allwork .space.
