Summary of the Interview

This interview features Will Abbey, Chief Commercial Officer at Arm, in conversation with David Savage, Tech Evangelist at Harvey Nash. Together, they explore how AI is reshaping global industries, the skills needed to thrive in an AI driven economy, and the cultural and organisational shifts required for businesses to keep pace.

Will begins by outlining Arm’s pivotal role in the global technology ecosystem. As a UK headquartered but truly global business powering more than 300 billion devices, Arm positions itself as an AI first company, enabling everything from data centres to mobile devices to run AI workloads efficiently. 

A central theme of the conversation is the AI readiness gap. While Arm reports that more than 80 percent of its engineering workforce already uses AI tools across design, testing and validation, a broader industry statistic suggests that 50 percent of workers lack even basic digital skills needed to be AI literate. Will suggests that appetite for learning is universal, but access to infrastructure, training and partnerships is uneven, leaving many organisations behind.

They discuss the UK government’s headline claim that the skills gap between a 55 year old and a 35 year old could be closed with two and a half hours of training. Will acknowledges the good intention but stresses that genuine AI capability requires far more depth, including understanding programming fundamentals, Python, machine learning principles and database skills.

Another key theme is productivity transformation. Will explains how AI now automates large parts of regression testing, debugging and documentation, freeing engineers to focus on creative problem solving and innovation. Similar gains are emerging in commercial teams, from virtual support engineers to automated quote generation that removes manual admin from salespeople. 

The conversation also explores the wider tension between rising demand for AI skills and the limited investment many organisations make in developing their people. Will notes that although some markets lag behind, the companies and governments he works with globally are increasingly committed to equipping workers with the skills needed to harness AI’s potential. 

The interview ends on the human impact. Will recognises that employees naturally worry about what AI means for job security but argues that AI should be seen as an assistant rather than a replacement. Just as the internet unlocked waves of innovation and new opportunities, he believes AI will expand what people can achieve, provided organisations invest in ethical use, skills development and responsible deployment. 

Key Themes Discussed

  • Arm’s position as an AI first global tech company powering billions of devices

  • The AI skills readiness gap, and why foundational literacy must go deeper than short training courses

  • How AI is transforming engineering workflows through automation and productivity gains

  • The cultural and organisational barriers preventing many companies from investing in their people

  • Global differences in AI adoption and government support

  • The human impact of AI, including concerns around job security and the importance of reskilling

  • The need for ethical, responsible AI development across industry

Tech Flix 6 documentary

This interview is part of Harvey Nash’s latest Tech Flix documentary, which explores the AI paradox: AI is scaling, skills are not. The film examines how AI is transforming work, education, and regional economies, while asking a fundamental question:

Are we preparing people for the future, or leaving them behind?

Watch the full Tech Flix 6 documentary here.

Full Transcript 

David Savage 00:00

First of all, Will, thank you very much for taking the time to join me on this call. It's lovely to see you again having sat in person with you just a few weeks ago in London. 

Will Abbey 00:08

Yeah, no, it's a pleasure to see you again. It would be better if we were in person, but through the power of technology, I still get the opportunity to connect from the comfort of California. So it's good to see you again, David.Are you enjoying the Californian sunshine? Today actually is not a great day. It's still relatively warm, but I think as the sun will peak out around midday, so it will get warmer. 

David Savage 00:35

Look, before we get into anything else, I think it would be really useful just to frame who ARM are as a business for anyone who's unfamiliar. 

Will Abbey 00:43

Yeah, so, you know, we're a UK company. We are a technology platform provider from the data centers that operate, that drive all the content that you and I use all the way through to mobile devices, to sensors in the home. And AI sits at the heart of everything that we do. We are a AI first company.We ship roughly 32 billion devices. A quarter, cumulatively now, we're across the threshold of 300 billion devices, 8,000 people, presence worldwide. And I think AI would not function without arm. So think about AI. It's synonymous with arm. AI runs on arm, and arm runs on AI. 

David Savage 01:40

So you mentioned there are 300 billion devices, and you say that ARM are an AI-ready business. It's been put to me that 50% of workers today don't even have the basic tech skills needed to be skilled in AI.Given ARM's global position, I mean, I know you've said you're a UK business, but you are also a leading global tech business, how would you surmise the state of the current workforce globally? Look, I mean... 

Will Abbey 02:08

Let's start closer to home. So firstly, you know, readiness varies dramatically by markets and industry.I don't think there's any single picture of global preparedness and prepared and readiness. But when I think about where Arm finds itself, you know, we're about 8,000 strong in terms of a workforce, we across the engineering discipline, I would say 83, 85% of engineers within Arm are using AI tools, using AI principles from the hardware and software that we develop to even my own team in terms of practical things around support, practical things around preparing quotes for our partners, so, you know, we are AI ready. 

David Savage 03:08

Why do you think it is then that we've got this 50% stat that we're hearing? And that was from IBM, and they're driving IBM SkillsBuild.It was from an interview I did earlier this year. You say you are ready. That's fantastic to hear, but why is it that so many other firms, it would appear and not in that position? 

Will Abbey 03:25

I can't speak for every firm, right? But I think appetite to learn is universal, but access to infrastructure and then the practical enablement still remains uneven.I keep coming back to Arm. It's a journey that we've been on. We knew exactly where we wanted to get to and we've partnered with, you know, large companies like OpenAI. And so it isn't just having a desire to want to use AI within your organization. It's taking practical steps and partnering with companies that can enable you to get to where you want to get to. The journey is being slow, but it's been prudent. And we've got to a place now where across the engineering discipline, from design to testing to validation, AI is being utilized across all of those disciplines. Look, I can't speak for every organization out there, but I think for me and for Arm, it's about looking at productivity gains and then perhaps even beyond productivity gains. How do we get to the place where we're doing something fundamentally revolutionary with respect to AI? And so it works for us, works for Arm. And I'm sure there are companies out there that are embarking on the same journey. It takes focus. It takes a willingness to get things done. And I think we're doing the right things from an Arm perspective. 

David Savage 04:50

I don't know why the UK government picked out 55-year-olds and 35-year-olds. OK, I'm just going to say that before I launch into this question.But the UK government suggested that to close those foundational AI skills, that they believe the general population needs to thrive in the workplace of the future. It would take just two and a half hours worth of training to close a gap between a 55-year-old and a 35-year-old. Do you think that gives the right kind of narrow focus we need to build basic AI literacy? Or does it risk falling short of the deep knowledge and providing the platform for continuous learning that people really need to thrive in modern organisations? 

Will Abbey 05:33

Yeah, I mean, first, I want to commend the UK government for at least being bold enough to acknowledge one, there is a skills gap and then, you know, putting out a sound bite around two and a half hours. And in some respects, I can see where that could make sense.But again, you know, AI readiness, I think there's an arc, you know, from a point of view where I'm just perhaps being digital aware, knowing how to use a large language model. Throwing information in that large language model and getting some useful information back. And so perhaps that two and a half hours is really used that, you know, taking people are in their fifties and just making them comfortable as to this is what an LLM is. This is how to utilize it, and this is how to engage with it. But then when you look at the other arc of sort of productivity and usefulness from an industry perspective, two and a half hours isn't sufficient. And so when you start to think about the fact that, you know, you still need to have a fundamental understanding of something like Python, which is the programming language that engineers would utilize to engage and interact with an AI machine. And so there's that there's also fundamentals around machine learning as fundamentals around, you know, programming languages around, you know, what is a what is a loop, what is a function. And so those things take a little bit longer than two and a half hours.But I think, again, it comes back to a desire and an intent. Once that desire and intent is there, it's a combination of governments, industry and technology coming together to make sure that the workforce is fundamentally ready to embrace this AI promise, which is real and it's here and it's it will make a profound difference to companies and make a profound difference to governments. 

David Savage 07:41

It's interesting that you talk there about some of the more traditional roles within a technology organisation. Our investigation has led to some conversations with technology leaders where they make the analogy of kind of a racing team and they talk about users as the drivers and the engineers as people who really understand what's going on under the hood and they talk about the fundamentals that are needed for AI with regards to testing and some of the more traditional skills that I think many people in technology would be familiar with.From your perspective as an organisation, what are some of those non-negotiables when it comes to hard skills that are going to enable someone to thrive in the future workforce and when AI comes in, delivering on its promise? 

Will Abbey 08:25

Yeah, David, we sort of touched on answers to that in the previous question, you know, the idea that, you know, if you're a black belt user, if you, in essence, are producing a productivity tool around AI, you know, firstly, you know, the way in which models work, which chat boxes operate, they still need to be programmed. And so you need a programming language. And so Python is the language of choice, you still need to have an understanding of what, you know, what a programming flow is, what a function is, what a loop is, what a variable is. And so those are those non-negotiables around programming and understanding programming, understanding how database works, things like SQL, how to manipulate data, because at the end of the day, AI is all about data, like data manipulation, data extraction. And so those principles are key. And then, you know, machine learning, it's still a discipline that we look for when we bring on AI experts. And so I would say those are the three fundamentals, three non-negotiables. So the idea of understanding a programming language like Python, understanding machine learning, I think that's a prerequisite. And then, you know, I'd say that the third is really just understanding databases. And so if you've got those three disciplines, we and many organizations can put you at a task where you can be super productive in understanding and deriving some outcomes that are beneficial for your organization.And then, when I look at what we're doing at ARM, you know, we're seeing some real significant improvements from a productivity perspective. When you think about hardware and software design, what has limited the industry for some time is things like regressive testing of code, whether that's hardware, whether that's software. And so the practicality of an AI-first approach means that rather than billions and lines of code where an engineer simply needs to kind of scroll through that code to identify potential bugs, you can essentially set up a script, set up an environment whereby overnight that regression testing is being done by an AI tool. And so when you come back, well, firstly, it means that you're not having to run endless sort of compute cycles because the problem area becomes narrow. But the engineer then gets the opportunity to kind of pinpoint where the problem area lies. And so from design, from testing, from debugging, we're seeing some practical productivity outcomes from the way in which we're using AI.And then I guess ultimately, the holy grail for ARM is not just productivity improvements, but can we get to a place where we can do something fundamentally revolutionary with CPU design, right? You know, can we do something that means that an AI could be ultimately used in helping engineers build better products using novel techniques. 

David Savage 11:39

It's interesting to pick up on your final point there. Talk about the productivity gains.I suppose, what space has that created for people in their jobs? You'd say there about, we can tackle some really exciting problems, but fundamentally, what has that done to the job that people are doing for you day to day? 

Will Abbey 11:57

Yeah so that's a great question and you know I've sort of left the dark side of engineering a long time ago but you know in any design discipline the piece that engineers tend to not like is the documentation it's the debugging it's the verification and so you know a significant portion of an engineer's time it could be 30% it could be 40% is doing I want to use the word tedious tasks super important tasks but they can be tedious looking through lines of codes and identifying common errors right meaningful errors and so that's what that's what AI within arm is doing and so if I can now create 30 40 percent of time and give that back to an engineer to do more design orientated tasks it's it's a positive outcome and so you think about six seven thousand engineers where you're essentially giving back 30 40 percent of creative time to engineering well that that's that's that's a good outcome it's a good outcome for arm and I think it's a good outcome for the semiconductor industry

David Savage 13:08

Look, you're chief commercial officer of Arm, and yes, we're talking through the lens of technology, but do you feel that that enthusiasm, that optimism is shared across all functions within Arm? Because AI is obviously disrupting technology roles, but it's going far beyond that at the same time. 

Will Abbey 13:25

Yeah, we spent a significant amount of time talking about the engineering benefits and as an engineering organization, that is the rightful place for us to focus time. But I still run a large global operation.And so we're already, within my own team, we're already making best use of AI techniques and AI productivity tools. Look, I'll give you a couple of really clear examples. So the support organization, which I'm responsible for, this is the team of individuals that work with our partners to co-create value. And so the way in which that organization work, we've created this thing called virtual field applications engineers. And so our partners can interact with a bot that essentially helps them develop products quicker and more meaningful without having to call a human individual to get support and assistance. The other area that we're trialing right now, which I'm super excited about, is the whole area of quote generation. So typically a salesperson comes back from a call. He then has to essentially create a proposal. And the way that he does that can be somewhat manual in the way in which they would operate with a database. And so we're automating all of that, making the life of a salesperson that much more productive by going back into the archives, digging out the previous quotations, and just making it easier and simpler and more productive for a sales engineer to interact with our partners.And so it's not just an engineering benefit. We're also using it in the commercial aspects of the business that I'm responsible for. 

David Savage 15:15

My background in work before this particular solid job was as a salesperson and I can absolutely tell you from experience that most salespeople hate admin. 

Will Abbey 15:27

Unfortunately, they do, but it's a necessary evil bullet. But again, imagine this 40%, 30% productivity gain.If I can spend, if the salesperson can spend more time in front of the client, rather than being in the office, clicking this, clicking that to generate a quote. He simply just interacts with an agent. He describes the experience that he's had. He requests a quote, and hey presto, the quote's produced linking in any history that's available on databases from previous quotes, from previous sort of interactions with a customer. Again, allows customers, allows my team to focus on the value hard of being in front of customers rather than back of office generating paperwork and quotation. 

David Savage 16:14

Nash Squared's research points to this 82% surge in demand for AI skills, and I think that's largely generous of AI skills, but nonetheless 82% surge year on year in demand. And yet at the same time, we see 50% of organisations, give or take, not investing in their staff, showing little or no investment in their staff internally.Why is that paradox persisting? Why is it that there is such high demand, yet such low investment in people? What cultural or commercial shifts in business leader thinking needs to happen, if we're going to try and tackle that? 

Will Abbey 16:52

Yeah, I mean, so look, I've seen the opposite in the companies and organizations that I interact with, and perhaps because, you know, no single panacea for this problem, because markets are different, geographies are different, governments and our governments interact with companies are different. And I think, you know, I can see perhaps at the extreme end of the scale, companies that perhaps are smaller in nature, are still focused on manual tasks, are still really trying to eke out margins in terms of what they do, and perhaps are not investing heavily enough in their workforce from an AI readiness, but from the, you know, from the technology sort of angle, the companies that I spend the bulk of my time interacting with, whether it's here in California, whether it's in Malaysia, in the Far East, whether it's in North America, I think that the promise of the benefits of AI are so profound that companies are equipping their workforce to make good on this really exciting and this really powerful trend, and the benefits are huge.

18 mins 17

I think in the previous podcast, you know, you and I talked about the work that ARM is doing in places like South Korea, the work that ARM is doing in places like Malaysia, and again, we're not doing it by ourselves. Is governments recognizing that this thing is real? Governments recognizing that they want to prepare and uplift their workforce to make good on this promise of AI which is real, and so 

18 mins 42

maybe, you know, from the lens that I look at this challenge, I'm seeing positive outcomes, and perhaps there's a delayed effect, and so some of the slower-moving economies haven't quite braced themselves yet for this real promise which is in front of us, but I think they will.I think they will, and I believe they will. 

David Savage 19:00

One last thing I want to ask you, then. This film is fundamentally focused on the human experience. And look, fundamentally, I agree with you that AI holds huge promise. And when you talk to an individual on most occasions, they will say, oh, yeah, this particular tool is fantastic. It helps me do x in my job. I think most people think that this is a net positive.However, you lead an organization of 7,000 engineers, I think you said. And 

19 mins 27

I cannot believe that you've not had some people come up to you concerned about what AI might do for their roles in the future. 

19 mins 38

When there are those totally normal, totally human concerns about the role of AI on future work opportunities, what do you say back to people? 

Will Abbey 19:47

You know, there's this notion of vibing, right? This idea of AIs that can generate code and, you know, lots being talked about that in the press. And so when you start to look at that, you think, okay, you know, the machines are coming to take over our jobs, right? They're going to produce code. They're going to produce hardware. And then by definition, what do we as humans now do, right? The reality of it is that the code that's been produced is good enough to get started, right? And perhaps over time, it'll get even better. But again, the idea here is not replace the human engineer, but assist the human engineer with a first-past sort of platform for that individual to iterate on. And again, the productivity improvements that a vibe code generator will produce means that engineers can do more work, but perhaps I'm an eternal optimist.But I don't see it as this dark end of engineering, the machines are taking over. I don't think that's the reality of what we're going to see.

21 mins 02

 You know, a similar concern was raised around, you know, the whole internet, right? And what was going to happen there? The reality is that there's been more productivity outcomes, more innovations being created, more startups have been born, more economies of scale as a consequence of the internet. And I think we're going to see something very, very similar. Look, the reality is that people need to, and people need to, and organizations need to assist people in being equipped with the new skills that are necessary to become productive in this new area. But I don't see it as doom and gloom. I think it's going to be a positive outcome for the industry. I think it's going to be a GDP driver for governments and economies that focus on embracing this tool as opposed to heading the sand, it's all dark, it's all doom and gloom, we should hide from it.That said, I do think that, you know, the idea of thinking about ethics needs to be thought through very, very carefully and managed very, very carefully. And, but that is a cautionary tale that perhaps is for another conversation. But this thing, I don't see it as doom and gloom. I see it as a catalyst for growth. And that's why ARM, we're embracing it. And that's why it's making meaningful differences to the way in which we operate and the work that we're doing here at ARM. 

David Savage 22:28

Well, it's been a pleasure to catch up with you and speak with you again. Thank you very much for giving up some time today. 

Will Abbey 22:32

Anytime David, it's always a joy and a pleasure to talk to you.