In the New York Times, the ever-cautious Paul Krugman insists that business forecasters should proceed cautiously in correlating the popularity of AI with a tsunami of economic growth. “That’s not to say that artificial intelligence won’t have huge economic impacts,” he writes. “But history suggests that they won’t come quickly. ChatGPT and whatever follows are probably an economic story for the 2030s, not for the next few years.”

Finally, some common sense about Big, Bad AI. Over here in the land of visionary leadership, we’ve watched with chagrin for about two years as pundits somehow decided that the ability to use artificial intelligence to write college term papers equals the obsolescence of the bone-and-meat workforce…and, possibly, the Rise of the Machines. Flippancy aside (and Gosh knows, we love being flippant), AI really is a big deal for productivity, predictive analytics, and automating repetitive tasks, not to mention content creation. But our purview is corporate vision, peering into the hazy future to find landmarks and shape what’s coming…before someone else gets there first.

Tech experts and business analysts are burning terabytes worth of pixels to make sense of the impact of AI. Still, much of said impact comes down to the same applications: automation, market segmentation, content, hiring, and even predictive problem-solving for customer service departments. Cool, but those are tactical approaches addressing on-the-ground, in-the-moment needs. Vision is strategic and evolutionary, plotting out the optimal ways an organization and its offerings can and should change to disrupt and ambush the competition.

The genius and efficacy of artificial intelligence lie in hoovering up ridiculous amounts of data and identifying meaningful patterns. But what can deep learning algorithms do when there is no precedent, no pattern? Here are five ways AI might impact the development and execution of your corporate vision even when there’s no path to follow:

Market predictions.

One of the most nerve-wracking aspects of executing a vision is wondering if the market will have moved on by the time your vision is ready to go public. By processing real-time data from various sources—economic and financial reports, consumption data, customer reviews, and spending trends—AI can empower leaders to anticipate market shifts and adapt swiftly to changing circumstances. This agility is crucial for long-term vision execution because it lets you recalibrate your strategies in real time and stay ahead of the curve instead of reacting.

Provoking innovation.

Every organization wants to be an innovator in its field, but few are genuinely innovative because innovation is challenging. AI can facilitate fast communication and information sharing within development teams, but that’s not all. Machine learning algorithms can sift through vast amounts of information to identify emerging technologies and unique applications for existing technologies—as well as failures, litigation, and other indicators that a technology might not be worth pursuing. AI can act as an innovation filter, delivering a steady flow of new ideas to creative departments while helping them avoid stagnation and distractions.

Fear of automation.

Not every impact of AI will be positive. As technology becomes more firmly entrenched as a tool of your vision’s development, some employees will become apprehensive about their jobs. Everyone knows that one of the main benefits of AI is that routine and repetitive tasks that once consumed valuable time—data entry, analysis, and even customer service—can be automated, freeing up people and resources for more strategic endeavors. But this efficiency boost could create an atmosphere of anxiety that might sabotage the daring, visionary culture you’re trying to make. Leaders must account for the human impact of AI and proactively engage with personnel whose work could be turned over to algorithms, letting them know they still have a place in the organization. “Automation anxiety” could become an asset if it leads to closer communication and more profound empathy in the organization.

Algorithmic bias.

Finally, if you rely on AI for predictive analytics and market analysis, you will encounter systematic bias in the algorithms that make AI run. These come from the biases of the humans who program and “teach” the AI systems. Still, they can be detrimental to your organization if they turn you aside from specific strategic options from hiring a more diverse workforce. Remember that AI is no substitute for human judgment and intuition; review all AI recommendations for hints of bias and ensure that you’re going into the future clear-eyed.

AI is poised to revolutionize the execution of visionary strategies, enabling corporate visionaries to foresee the future and proactively shape it, fostering a new era of dynamic and responsive leadership. It still won’t turn every leader into a bold visionary, but it will undoubtedly help leaders bring their visions to life in more manageable and humanistic ways.