Let’s start with the premise that change is hard for everyone. For large organizations, it’s even harder the bigger the organization. Over the past 15 years, as we’ve watched large organizations try to embrace mobile, big data, cloud, and general digital transformation, we’ve seen many organizations continue to struggle with implementing these technologies. Today, whether businesses and employees like it or not, AI is forcing change.
Part of the problem is technical debt, the idea that an organization’s technology stack needs to evolve to take full advantage of new technologies instead of relying on a set of technical capabilities designed for the previous era. It’s not easy to try to change something fundamental about how a business operates without risking breaking something that already works well. Few managers are willing to embrace that kind of change. Real change carries enormous risk and enormous potential.
Another part of the problem is institutional impotence. It’s hard to change the way people do things. Let me tell you a story from when I was a technology writer a few years ago. We implemented a computer system in a small town registry of deeds. The deeds in the town were written on paper and stored in a cabinet. It was manual and cumbersome, and it could take weeks to track the deeds because people had to manually dig through the paper swamp.
The computer system was obviously better, but the front desk staff who dealt with the public were not sold. Part of their job was to stamp rubber stamps on completed documents, which they did with great enthusiasm and then sent the documents to the filing cabinet. For these employees who had worked at the counter for 20 or 30 years, the stamp symbolized their identity and sense of power. They did not want to give it up.
Eventually the system designers just gave in and let them keep their stamps. They were no longer needed for the online system, but they accepted the change.
Here we come to the biggest problem of all: change management. The hardest part of implementing new technology is not shopping, buying, testing, and implementing. It’s getting people to use it, and often, not having them maintain their own traces can thwart even the best intentions of the team implementing the solution.
When you think about all of this, and the level of change that AI is bringing, you see a much more radical adjustment to the way we work on the horizon. Those who hold the stamps will see their power disappear, and they need to be careful not to alienate them, or else they could end up throwing their money down the drain.
Ultimately, organizations are people, and people are messy, and we need to look beyond technology to the end goal: implementing new software that can transform the business.
AI is a whole new way of working
Large-scale technological change within organizations is not new. The advent of the personal computer in the 1980s and the rise of spreadsheets and word processors were among such moments. The Internet and the World Wide Web were others, but AI could be even bigger than the previous wave of change.
“The Internet era lowered the cost of information transmission, and CIOs rode that wave to bring digital technologies into their organizations. But AI is a very different type of technology. It’s lowering the cost of expertise,” Karim Lakhani, faculty director of Harvard’s Digital Data Design Lab, told TechCrunch.
Box CEO Aaron Levie went even further, saying that this is the first time computers are doing what people used to do, and not helping people do it more efficiently. “So it’s a new relationship with computers, because they’re making judgment calls. They’re evaluating information. They’re processing our data like humans do,” Levie said, and the company needs to rethink the role of computing in its organizations.
“There’s a whole new framework and paradigm that we have to evolve as a result of what AI can do in the enterprise,” he said. That means thinking about how this technology will impact the entire organization, looking at issues like answer accuracy, data leaks, and the data used to train models.
Of course, Levy believes that his platform is built to solve these problems and help customers solve their own, but businesses often find themselves dealing with multiple suppliers who tell similar stories, which tends to make it harder to find the ones that can truly help and add value.
Does this work?
One of the big challenges organizations face is figuring out whether generative AI is actually delivering on its promise of productivity gains. There is currently no good way to directly link GenAI capabilities to productivity gains. This makes it harder to sell internally to skeptical workers who may be concerned about their future as they implement AI.
On the other hand, there will be employees who demand these new tools, and this tension can further increase organizational stress as managers struggle to figure out how to implement AI across the company, with varying opinions about the impact on their work.
Some, like Jamin Ball, a partner at Altimeter Capital, have written that the technology is so transformative that companies should jump on it whether or not they see immediate benefits. “The world is evolving right now,” he wrote in the Clouded Judgement newsletter in July. “AI is a massive platform shift. And if you don’t adopt it or invest in it, you risk losing market share and slowly becoming irrelevant.”
Gartner analyst Rita Sallam says that when you look back at the first word processors, the value proposition had nothing to do with saving money by eliminating the secretarial pool. It helped create new ways of working, and AI offers a similar value proposition.
“Getting rid of the secretarial pool probably didn’t justify the cost, but when you take away the physical constraints of writing down ideas and iterating on them, and put that out there for everyone in the organization, you open up an era of potential innovation, even if you can’t prove it, and people now have the ability to organize their thoughts in a completely different way,” she said. That kind of change is hard to measure, but it’s a huge benefit nonetheless.
Getting executive buy-in has always been a critical piece of the digital transformation puzzle. Like the PC before it, the cloud has changed the way companies do business.
Lakhani says AI is different from the cloud because of what CEOs can achieve with it. You don’t need a real technical explanation to see the power of AI, and it can help drive change within your organization. “I think what’s different and what’s accelerating the hype is that CEOs in Davos, board members, people who influence corporate strategy, they can now access these tools and see some of their problems being solved in this way,” he said.
But that doesn’t mean vendors can just dump solutions into organizations and sell them. They have to figure out how to demonstrate value. “Hyperscalers and vendors have to do a better job of demonstrating how organizations can actually adopt these things,” he said.
But overcoming the people problem will be an even bigger hurdle. Lakhani says there are three cliches that organizations should follow as they tackle this task. First, he says, “Machines will not replace humans, but humans with machines will replace humans without machines.” Second, he says, “If you don’t think of the change mandate from the top down and create incentives for the ‘stamp makers’ to actually adopt and feel good about what they’re doing, AI will fail at the front lines.” He says trying to force it will fail, so everyone needs to be defined how and why they need to change, and not use the “because I told you to” approach.
No one is saying this will be easy. Organizations vary in maturity and technological readiness. But people are people, and real change does not happen easily within large companies. It is no exaggeration to say that AI will test organizational flexibility more than any previous technology, and some companies will survive or die depending on how well they handle it.
