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We spoke to Tom Goodwin, futurist, transformation consultant, and tech optimist, to get his reaction to Teamwork.com’s report The Sprint to AI.
Tom’s hot take? Winning the AI race is less about speed, and more about pace, strategy, and keeping a cool head. Here’s 10 key learnings from our chat that offer a different perspective on AI and how it’s impacting client work.
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1. There’s no such thing as ‘AI’
Wait, what? Tom contextualises that: “...per se. The umbrella term of ‘AI’ is a catch all for an unbelievably vague collection of technologies, spanning generative tech but also includes things like really advanced automation and algorithmic decision-making. It’s not just one tangible thing.”
“AI is a broad tapestry of tools that together offers a new canvas of opportunity. Whether that’s accelerating what you’re already doing, or enabling new visions to come to life, it means a totally different way of doing things. And for that reason, I feel we are absolutely on the edge of a paradigm shift in how people work. So we need to be much, much more ambitious, empathetic, and imaginative about how we use it.”
2. AI is not a magic wand
Tom says, “I have quite a nuanced view about AI. Yes, it’s extraordinarily exciting. But at the same time, it’s going to take time to figure out, there will be missteps, and with that comes a degree of disappointment. We'll probably see a trough of disillusionment when people realise AI isn’t a magic wand for any and all problems — something the Teamwork.com report points out in the context of Frankenstacks.”
“A lot of people think that AI can compensate for an otherwise shaky business structure or legacy tech failings. I think the opposite is true. Technology is a multiplying force — it tends to exaggerate things. If you have an unbelievably well-formed company with smart people doing the right jobs in the right ways with the right tools, the right data, technology will amplify that to make it extraordinarily brilliant. But if you have a company with the wrong tools with the wrong structure with the wrong foundations you’ll simply get to a worse place, faster."
3. The early bird doesn’t always get the worm
Tom admits he used to be obsessed with this idea that everything was going to happen quickly. “The reality is that change tends to happen quite slowly. Institutions take time, regulations matter, and humans are quite risk averse. So I've really readjusted how quickly I expect things to change.”
In the race to AI, the real winners will be those who go at the right pace. He continues: “The idea that early adopters automatically get this huge headstart and leapfrog others isn’t always the case. If you look at the biggest, most successful tech companies today, they usually haven’t been ‘first’. They’re the ones that made moves at the right time — when the technology was good enough, fast enough, cheap enough, or when teething problems were resolved. This concept that you have to go really fast in order to win simply isn’t true”.
4. Don’t lose your head amid all the hype
“There's this unbelievable sense of pressure that companies need to show each other, and clients, and the trade media, and stakeholders, and the financial markets that they're on top of AI.” Tom says. “And what we’re seeing as a result is unbelievably rapid but superficial — in fact sometimes quite stupid innovation — around AI.”
He continues, “We need to have the confidence to say to the world, ‘We get this. We know it's going to be extremely profound. But let's do this properly.’ And doing it properly means figuring out what AI truly means for your business model. For your clients. For your long-term vision. For security risks, legal risks, regulatory risks, and creating a really mature and sensible and incredibly ambitious culture that brings people within an organization together. Done right, we really will see extraordinary value from AI. But that takes a lot of confidence and calmness at a time where it's incredibly difficult to behave that way."
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5. Start by stepping back
Tom notes “Typically businesses start in the wrong place. Often they look for a quick fix to broken systems and messy structures and hope that if we add enough layers of technology horsepower it will make sense of it.
A better approach is to take a few steps back. Figure out what foundations you need, where you want to be headed, why your company exists, and then start building around best-in-class software to deliver that vision. By far the most important question is what are we actually try to achieve here? But unfortunately, when new and exciting tech arrives on the scene, that process can seem quite boring compared to just getting stuck in and seeing if it can solve your more straightforward problems."
6. The opportunity cost of workarounds
“Poor technology isn't just miserable to work with — as the report shows, it actually loses you money” Tom points out. “We're really starting to see company leaders realize this, and recognize that technology is more than just a cost centre. But within that, a big challenge is that companies are operating with too many point solutions, and relying on people to be the glue that sticks those systems together.
The advent of AI is a confronting moment, because it’s forcing businesses to really look at this technical debt and the dysfunctional processes and workarounds that we’ve just come to accept as the norm. It’s an opportunity to replace incredibly old software with something new and best-in-class. Something that’s so powerful that you actually change the way that your company works around it. But that means not falling into the trap of using AI to create even more layers of workarounds, and instead unpick what’s causing them in the first place."
7. All that sparkles is not gold
“In the early days of a big technology breakthrough like AI, it’s typically applied in the easiest, fastest ways possible. But that’s actually a very bad way to improve a product and it doesn’t really offer anything transformative for the user. Surprisingly, it’s the smaller things that make a big difference. Dictation software. The ability to search within Apple photos for people, plants, or business cards.
Often the most dramatically helpful applications of AI are not the ones that appear to be sophisticated, but they appear to just make your normal life a little bit more easy. I think one of the most interesting things for me in the Teamwork.com report was just the idea that we can have more ambitious solutions that span many different tasks. As a consumer, you should be looking for technology that applies AI more meaningfully, in a profound and core way. That’s where we’ll see companies really leapfrog in how they perform."
8. Honesty is the best AI policy
“The AI transparency gap that Teamwork.com has identified is very real right now. On the one hand, clients want you to use AI to be faster and leaner. But it’s a bit of a Trojan horse, because it also makes people more demanding — and query your fees more. When it comes to transparency around AI use, my view is that honesty is the best way forward.
Position your AI use as something that allows your brilliant workforce to be even more brilliant. So rather than doubling down on the level of automation or the speed at which things can be done, companies should focus on the fact that they can now serve people better. Focus less on the AI as being the point of difference and more the fact that it happens to enable you to produce even better work — whether that's outputs, reporting, responsiveness, or compliance."
9. When it comes to AI in client work, focus on value
"We’re still in the early days of AI and when people don't know about something there's a huge risk they think it’s doing more work than it really is. So, if you're being asked to reduce your fees because of your use of AI you need to go in on the front foot, and focus on the value of the outputs you’re delivering.
The reality of a lawyer's job isn’t that they spend all day writing contracts. It's that they spend all day understanding the mentality of the judge, how to make a creative case, and how to lubricate relationships to find out more. The same can be said for working on complex projects, or with clients. The more that we celebrate what AI can do, often what we're really showing is that we don't understand how certain jobs work."
10. You’ll know AI is working when you’re not talking about it
Tom concludes: “There's a weird thing that happens with technology, which is when it really gets good, we tend to not notice it. We don't notice cell phone reception, except when we don't have it. We don't notice how much phone battery life has improved, unless it goes. I think the true sign that an AI application is here is that people just talk about products working really well rather than it being ‘AI powered’.”
“If I had to talk about a sort of defining characteristic for the next few years, I think it would be automation, making things automatically happen for us and increasing our ability to do more with less. For me the ultimate role of any software is to move away from being a specialized and deep point solution and to become something much more like an operating system. One that does things at a kind of task or a job level, rather than doing specific things it does everything and it orchestrates stuff together.”
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