I’ve been spending a lot of time this summer talking to marketing leaders about Artificial Intelligence (broadly speaking) and how they are weaving it into their work. And, I’ve been thinking about the other major tech-driven, hype cycles I’ve seen, from the first excitement about the web, the .com era, the Year 2000 problem, Web 2.0, Mobile, social, blockain, Web 3.0, Crypto and now AI.
They’re not all the same
I believe the AI era will be another epoch for business and organizations. In 30 years, we’ll look back on 2022 as the year that the AI era really took off in the US. It’s overlapping with the “Digital Transformation” era that begain in the mid-2000’s, and continues today. As AI innovation accelerates, whole industries will be created, new classes of products will be invented, new business models will arise to sell them, and new business functions will emerge to support it all. And, of course humans, culture and societal shifts will be driving all of this forward.
There are many, many folks that are fired up about what’s possible and are a little woozy with excitement over the role AI will play in helping organizations. They’ve seen how “digital” has driven better experiences, better products, new markets, new business models etc. And, they see AI as the latest chapter in the “Digital Era”.
While we’ve learned some hard and interesting lessons from the digital era, we can’t just rinse and repeat for AI. To quote someone I admire greatly, “The future does not fit in the containers of the past”.
I’m onboard for the AI ride. I’m choosing to focus on the potential good that may come through the innovation that will be unleashed. But, I’m also a part of the “Class of 2000”, a cohort of leaders were, for better or worse, on the leading edge of the digital era for business. We were there for the first internet boom of the late ‘90s, and we got busy (but realistic) after the bust. Many of us built up digital functions and then led digital transformation efforts at our corporate organizations. Or, we built consultancies that guided BigCos through transformational efforts as partners on the outside.
So, we’ve been through some hype cycles. On bad days, we sound like cranks and “grizzled”. On good days, digital X’ers can use some wisdom to avoid mistakes and guide teams through some choppy waters.
Do Not Go Fast; Do Not Break All the Things
I’m recommending business leaders make a conscious break with some of the principles they used to make decisions in the digital era. The main principle that will need to be abandoned in the AI epoch is the focus on speed over quality. So many leaders tried to adopt the “move fast and break stuff” ethos and, but I think that’s wrong approach for AI.
I would argue that business leaders should be pumping the brakes on major AI initiatives right now, and focus instead on their core “digital transformation” efforts and optimizing their existing investments in data and data quality. Every business leader should be in “observe, learn, experiment” mode with AI tools and concepts, but that’s only the prelude to larger efforts that should come later.
How the AI Epoch Will be Similar to The Digital Epoch
We can seek out some patterns from the digital epoch and learn from them. These won’t go away as the AI era unfolds and grows. Smart leaders will keep these principles in mind as they look ahead.
- Prioritize consumer experiences – Great experiences that solve real problems for users will still be differentiators. The way consumers interact with orgs will evolve quickly, and business should prioritize great (not just good) consumer experiences. A pretty good chatbot experience will still frustrate users, no matter how good the AI underneath it.
- Every function will be impacted – Businesses will probably start with consumer contact points, just like the digital era, but every function will eventually be forced to change. Some might even go away (i.e. call centers). Advertising is already being pulled into the AI era (thanks Google PMax!) and soon every function will be impacted.
- Innovation AND Optimization – Strategic leaders should be seeking opportunities for true innovation while trying to optimize what teams are already doing. Just like in the digital era, AI will make existing processes and capabilities more efficient and effective, but there will be opportunities for whole new products, new experiences, and potentially, new businesses. Leaders have to balance both those opportunities.
- Company culture will need to evolve fast – Organizations will struggle to get talent in place, just like in the digital era. They’ll seek smart partners and try to hire the right folks. But, ultimately, AI will require a change in the company culture: Incentives, assumptions, mindsets, behaviors, skills and capabilities. We’re just not sure what that’s going to look like yet.
How the AI Epoch Will be Different
While we can apply some patterns and themes from the digital era, we’ll have to acknowledge how this period will be different.
- Change at Higher Velocity – I think the pace of organizational change will have to be faster. New tools will. force a rethink about how we work, what we work on, what gets produced and how. And, organizations will be stressed to try to keep up with rapid change in consumer expectations. For instance, consumers will expect the natural language interfaces available to them (e.g. customer service chat bots or call center IVRs) to be as good as ChatGPT, Google and Siri. Internally, the intelligence of the tools will grow so fast, internal talent might not be able to understand what and why the AI-driven tools are doing what they’re doing. That’s probably going to create some existential crisis inside, for instance, some finance orgs.
- Collaboration Imperative – Keeping pace with the evolving tools and the emerging user expectations will force organizations to collaborate at light-speed on new methods, new policies, new benchmarks of quality. And unlike the digital era, where some groups could evolve alone, functional units will have to collaborate well to win. The new policies, data quality efforts, and fluency with the tools will have to happen together, immediately. Politics, misaligned objectives and incentives, and poor communication will have to be resolved much, much faster. Businesses won’t be able to use quarters or years as their corporate planning timeline, but weeks.
- Engineering power vs. creative craft – In the Digital Epoch, brands could “win” based on the quality and consistency of their user experiences and content. Companies had to innovate to create better experiences for users and consumers, but the defining difference was made by the art and craft of the UX design and the creative excellence and production quality of the content. In the Digital Epoch, the defining difference will be in the quality and consistency of the data, the volume of compute available and the finesse in the algorithms. Engineering will be the difference maker; UX will only make the experience more pleasant.
- More dangerous – Businesses will have to plan carefully for when they let the algorithms take over for the humans. The risk level inherent in AI driven experiences will be much higher, especially as AI gets woven into financial planning tools, mission critical customer experiences, and process automation. Businesses will be reliant on 3rd party software that uses AI that no one understands or will have time to test and vet. As the speed of integration ramps up, and more emerging tech goes into production without full testing, a much higher level of risk will be built into systems.
Learn Fast, Act Slow
The AI Epoch is just getting started. If we’re playing a long “game” of AI in business, the players haven’t even gotten to the field yet. We’re not even in the first inning. Whatever the metaphor is, it’s still early.
I’m still a tech optimist after all these years, but i’m, wary of a lot of the hype and I’m wary of business leaders who go too fast when they don’t understand the risks. When i’ve been asked recently what marketers and corporate leaders should be doing, my advice has been to, essentially, learn as much as you can, dabble with the tools on your personal time, and try to resist the urge to invest your team’s time. In other words, “Learn Fast, Act Slow”. There will be clarity on where to commit time and capital later.
