Art Zeile

As businesses increasingly turn to AI to drive efficiency and innovation, I've begun to consider the critical question of whether we are looking at AI risk in the right way.

I think it's fair to say that few innovations have sparked as much interest and debate as artificial intelligence (AI), the implications of which are unfolding at exciting speed. But when I look at what’s being done and even what’s being talked about, it strikes me that we don’t seem to be thinking outside of our usual sandboxes. What do I mean by this? We’re looking at AI as a shiny new thing to integrate into what we’re already doing. We’re exploring how it can make our current processes faster, our current fraud detection better, or our customer-service chatbots a little smarter. And it can do these things, but stopping there is also a waste of the true value of artificial intelligence.

It's hard to blame organizations for viewing it this way. Launching small tests, building unconnected vanity features, telling teams to “just start using it”: these are all safe enough bets. Companies are asking themselves: “What if we start big with AI and the outcome is disastrous and we have to roll everything back?” So, we skew toward safety. The point I want to make is that this path isn’t safe at all.

Restricting this transformative technology to the role of supporting existing operations, rather than enabling transformative change at a speed that quickly puts a business on an amazing trajectory, is the true danger here. When faced with an opportunity like AI, which can make operations “smarter” while massively increasing efficiencies and revenues, sometimes the biggest risk is inaction.

If we are going to truly capitalize on AI's capabilities, we must shift our perspective and leverage AI not just as a tool for efficiency, but as a catalyst— the catalyst — for innovation.

Risk and Reward

What if, instead of merely enhancing efficiency, we took a closer, deeper, and more ambitious look at AI and its potential to drive significant innovation, opening new avenues for growth and competitive advantages?

Imagine AI-powered systems that go beyond automation to deliver personalized customer experiences, predict market trends, and automate complex workflows. And no, we’re not talking Google-sized “moonshots” that would require many millions of dollars—even billions—to actualize. We’re talking about realistic but sizable commitments. In fact, it can be something as straightforward as figuring out the right combination of AI vendors’ tools that will complement and enhance your current operations.

But ‘straightforward’ doesn’t necessarily mean easy. This level of integration requires a fundamental rethinking of business models, where AI becomes central to the strategy rather than an auxiliary component. Of course, with the great power of AI come significant risks, and if we're going to tap into its transformative potential, those risks need to be managed thoughtfully. The organizations successfully embracing AI spend a long time in careful planning before they make their AI decisions, which is a terrific way to mitigate risk.

To navigate these waters, it’s helpful to break down AI risks into distinct categories, each with its own set of pros and cons.

Let's explore these risk categories and the different approaches businesses can take, on a spectrum starting from doing nothing to the opposite end, going all-in:

Inaction : Some companies are choosing to adopt a wait-and-see approach, avoiding the initial costs and uncertainties associated with AI adoption. There’s some wisdom in approaching new things this way, especially when it comes to projects that will be expensive from a tech and people standpoint. Many a company has been burned by embracing a tech fad such as “web3” or mixed reality too quickly. But AI is no fad, given the rate at which it’s already transforming how we live, work and play. As I mentioned before, the biggest risk in this crucial AI moment is sitting back and allowing yourself to become obsolete as more ambitious companies quickly adapt to the evolving environment... and use their new AI tools and workflows to take your customers, market-share, and revenue.

Cautious Pilot Approach : Another common strategy is to implement AI on a small scale, running pilot projects to test its capabilities and impact. This approach allows businesses to learn and adapt without committing significant resources upfront. While this isn’t as risky as total inaction, the downside is that these pilots often remain siloed and fail to scale, which limits their overall impact. The cautious approach also risks missing out on the larger opportunities AI presents.

Test-and-Learn : A more proactive strategy involves actively experimenting with AI across various parts of the business, learning from successes and failures. This iterative approach can drive innovation and uncover new applications for AI. If you're going to go down this path, you need it to build a culture of agility—which you should be doing anyway—and find the will to embrace uncertainty. While this is better than the cautious pilot approach, the main risk here is the potential for resource drain without clear returns if not managed properly; you must constantly evaluate progress, and be ready to break the project very quickly from its “silo” for broader implementation once you’ve found a configuration that works for your business.

All-In Approach : Finally, some organizations may choose to fully integrate AI into their core business strategy, rethinking their operations and business models around AI capabilities. It's a bold approach that can cement your reputation as a leader in its industry, driving significant competitive advantages. This strategy is also the highest-risk approach, requiring substantial investment and the need for strong change management if you want to execute successfully.

Shifting Minds to Unlock Potential

The way I see it, at the heart of any successful AI strategy is the need for a shift in mindset from AI as mere efficiency tool to a strategic driver.

Making that shift requires courage and vision from business leaders and a willingness to invest in new capabilities, reengineer processes, and embrace the potential for failure as a pathway to success.

It's a truly transformative approach aimed at unlocking AI’s full potential, turning risks into opportunities for innovation and growth. You refuse to limit yourself to the same ultra-tight parameters as other companies with AI but proceed with an open-minded spirit of innovation and experimentation (and astute planning; given the expenses involved here, you need the framework of a plan before proceeding).

Most of us are at various stages of navigating an AI-driven landscape that is evolving every day, and while it seems natural to stay put while the ground is moving, the biggest risk could be playing it too safe—fortune favors the bold.

If you're simply integrating AI into existing frameworks, you're limiting your potential to harness AI’s true promise, and to truly thrive in the digital age, you're better off adopting a forward-thinking approach.

Here’s how I’d recommend building out your AI strategy quickly, embracing opportunities while mitigating as many downsides as possible:

Identify High-Impact Use Cases: Every company can potentially benefit from AI. Before doing anything, however, it’s important to figure out how AI will align with your specific business needs and strategy.

Acquire Leading-Edge Tools: Which AI tools will enable you to effectively seize those opportunities?

Embed AI in Development: Tech professionals and other workers throughout your organization should figure out how to integrate AI on a tactical level into the tech stack and products.

Analyze Early Wins: Feedback is crucial.

Transparent Communication: Communicate the company's AI strategy to all stakeholders and employees. When you’re moving at speed, it’s important to take a highly ethical, transparent approach to deploying AI.

We're just at the start of the great AI rollercoaster ride, and I encourage you to consider how this technology can drive innovation on a company-wide level, help you redefine business models, and create new value.

This is Part 1 of my LinkedIn series: From Calculated Risks to Quantum Leaps: Charting the Course for Tech Talent in Flux .

You can read the next article here .

Most importantly, please join the conversation and share a comment below.

Art Zeile

Denver, Colorado, United States 3K followers 500+ connections

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NBH Bank (NYSE: NBHC)

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