AI Democratized Innovation; Here's Why That Makes Intentional Innovation Even More Important

Robbie Morrison, CEO of Velosio, is a technology leader with 30+ years of experience driving business success through innovative solutions.

getty​The ability to innovate has drastically changed thanks to artificial intelligence (AI). With AI, more people have access to tools that allow for faster ideation, execution, refinement and multitasking. I’ve seen teams get things done in a week that used to take a full calendar year.

With such a vastly different innovation landscape at nearly everyone’s fingertips, it has become an ever-present temptation to simply put an AI wrapper around every problem. It even works, sometimes.

But mindless problem-solving with an AI bandage will not create truly distinctive, or even truly innovative, organizations. Organizations that adopt technology without understanding how that technology enables innovation will struggle, at best, or, more likely, fall behind competitors that move with greater intention.

Intentional innovation is the competitive advantage every organization needs to master to withstand disruption and thrive in business today.

Successful organizations are deliberate and thoughtful in how they approach innovation. And with so much of modern innovation wrapped up in increasingly omnipresent AI tools, every employee is, potentially, an innovator. But those innovators need a practical, goal-driven strategy to make innovation last, one that is adopted widely and remains viable long term.

This type of intentional innovation starts with understanding where the real pain points are, then building solutions or offerings around the problems that actually matter to the end user. It is about asking the right questions, documenting the pain and helping users identify the constraints they might not even realize they operate under. Gartner has found that 45% of high AI maturity organizations keep their AI initiatives operational for at least three years.

There is something to be said for “slow and steady wins the race,” even in our AI era. Just make sure your organization’s slow-and-steady is truly goal-driven and deliberate, not a mask for stalling.

That’s why being agile in your AI project approach pays off. Small initiatives build into larger strategic plays, but you’ve gained credibility and value with small wins all along the way. Clear goal-setting sets the pace at every turn.

If AI innovation runs rogue without clear objectives, companies will end up riddled with more technical debt: disconnected, non-ROI-generating solutions. Make goals for your AI innovation. Grabbing easy but highly visible use cases that drive outsized impact is a good place to start before thoughtfully working through a list of chosen pain points.

A deliberate approach does not automatically mean innovation at a snail’s pace. Speed is, in many ways, still a mandate for survival in the AI business landscape. But there is a difference between hasty innovation and accelerated innovation: direction.

The best way to balance speed with intentionality is to give it a specific direction. Create a path with small, measured projects that each solve specific problems. Iterate, stay agile and always know what you are trying to accomplish. Technology has always been best served when you already have a well-run process and then add technology to speed up the people side of work.

AI is no different. It can make workflows faster and more flexible for employees and clients alike, but you must know where you want it to go before you can channel its power. Steer AI’s knack for speedy innovation with clear direction, and you get exceptional acceleration.

While organizations work through their prioritized list of tactical AI wins, the especially wise ones will also maintain a group of curious experimenters. These are likely your first-in-line adopters, and perhaps the group just behind them: people who see the vision and become enthusiastic.

Geoff Woods’ The AI-Driven Leader calls these groups Innovators and Early Adopters. If an organization can get these first two layers of users to climb aboard and play with AI curiosity, the early and late majorities can be more easily swayed when widespread adoption comes.

This curious experimenter group is all about catching mistakes, working through early unexpected results—hello, hallucinations—and minimizing adoption pains. They are sifting through the growing pains so your hardest-to-reach users do not have to.

The value of keeping doors wide open for testing the unknown frontiers of AI is that your organization will be more ready to adopt the next big thing when it becomes viable. You will have users who are already familiar with the tools and working through the kinks, speeding up rollout and adoption across the rest of the organization.

AI is certainly an ever-present and enticing technology bandage, but the real competitive advantage does not lie in gobbling up every possible use case. Distinction will come to the organizations that tackle one clear innovation goal at a time, with the focus, discipline and curiosity to keep improving.

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