How AI Will Continue To Be a Force for Change in the Business Landscape

The rise of artificial intelligence use cases has been meteoric. And in many ways, a meteor is the perfect metaphor for the suddenness with which AI has reshaped the tech landscape. This relatively new technology is hurtling toward us, and we don't have the frameworks and models or the understanding to harness it.

We’re confronting this powerful technology with an outdated understanding. We’re coming from an industrial age and heading into an intelligence age where a technology has the ability to solve its own problems — a technology that in some ways is smarter, faster and better than us. That’s unsettling at the human level, and when we start folding that into our society, our culture and our work environment, so many unknowns will emerge: What’s going to happen to my job? What’s going to happen to my company? What’s going to happen to my stock valuation?

Yet even with this level of uncertainty, organizations of every kind are adopting AI with confidence. Recently, 90% of respondents to a CDW survey expressed that they are either “somewhat confident” or “very confident” in their organization’s ability to plan for and implement new AI solutions.

The level of confidence people have in their ability to implement AI comes down to defining terms. What is the AI that we’re talking about? We’ve been implementing AI for a long time. We have Siri on our phones. We have predictive text when we’re searching in Google or messaging. So, what do we mean by AI?

The respondents to our survey indicated that the most common use cases being implemented are around data analysis, security and fraud detection. And yes, we can roll out AI successfully across all of these different platforms, across our ticketing system, across our collaboration systems and across our customer relationship management systems. There are any number of places that we can roll out AI and feel confident in doing that. But is that a strategy or a tactic? Is that business transformation, or is that just operationalizing one part of day-to-day work?

According to the survey, 75% of respondents have a documented AI strategy in place. But what is your business strategy? What is the business outcome that you’re looking for? What is the future state of your business and your industry a year from now? Three years from now?

Fortunately, there are tools available to help build on your AI strategy and increase the likelihood of success for AI projects. We have a suite of frameworks within CDW’s Mastering Operational AI Transformation (MOAT) program. We have a reference architecture, a use case analysis and use case backlog. These tools are going to surface areas where there’s new work to be done to make your organization AI ready and AI successful. Then, you can combine that with the backlog of use cases you’ll start leveraging. When you pull people from every part of the company — from marketing and sales to operations and administration — into an ideation session for AI use cases, you’re going to come out with hundreds or thousands of use cases.

Respondents to the survey indicated that only one-third of their highest-priority AI projects have been achieved full deployment. And for projects that failed, some of the commonly cited causes included an insufficient understanding of AI’s capabilities, as well as a lack of clear leadership.

When we embark on an organization’s AI journey through our MOAT program, they often tell us, “We see AI, and we see all of these capabilities. We don’t fully understand what it means, and we’re frozen, we’re stuck. We need to get unstuck.”

We frequently begin by going to leadership with a simple question: What do your shareholders, your investors, whoever’s making money from your company, want to hear? That you have a really cool use case? Or do they want to hear that you have a comprehensive, thought-out business strategy to move forward into the next stage?

Once we have that initial conversation with leadership, they begin to understand. They know they need to be thinking 18 months down the road for the benefit of their shareholders. They start to recognize it as a human problem. And when you get down to the human element, there’s an uneasiness about it. There’s a lot of emotion around this technology. I’ve never seen anything like this before, but we need to address that part of it. People could knowingly or unknowingly sabotage our AI efforts. The 2024 Edelman Trust Barometer found that 35% of people reject AI initiatives.

The most useful way we’ve seen to help people deal with the emotions around AI is to talk about them, to validate them and bring it all out in the open. We have found that when people are able to talk about it, and when an organization has an idea of where it’s going with its AI strategy and business strategy, people may still feel uncomfortable with it, but they’re not resisting. They’re actually helping enable the AI in a better, safer, more secure way because those concerns are being folded into the design and the implementation.

I understand the high level of confidence survey respondents expressed in their ability to roll out AI. But this presupposes that the workflow and work process we have today will be the same and in place tomorrow. It’s important to challenge those presuppositions. Is this workflow still going to be relevant with AI tools in an AI age? So, instead of improving a legacy workflow application, maybe that whole workflow doesn’t make sense anymore, and we need to be able to challenge that. Keep in mind, we have AI agents now that can plan and collaborate as well as work with each other as an AI team.

I was looking recently at the speed that AI is moving. It occurred to me that we’re asking 20th-century Industrial Age questions of 22nd-century technology that came unexpectedly too early. We’re not asking the right questions of AI, so we’re not getting the right answers out of it. We need to rethink our assumptions about how things work, and now we have the opportunity to ideate with AI to ask better questions.

The reason I launched the MOAT program two years ago is that AI is not a business problem, and it’s not a technology problem; it’s a human problem. I looked at the capabilities of ChatGPT 3 at the time, and I immediately thought about what my kids’ future might look like in light of this technology transformation.

What keeps me awake at night is the impact it’s going to have on their future and their opportunities. There are two different paths it could go down: It could turn out to be really bad if we don't get it right, or it could be a golden age of abundance. That’s why I do what I do. I see that the leaders in our companies need to make the transformation, not only for business purposes, but for the next generation. We need to get it right for them.