It will come as a surprise to no one that AI is outgrowing the systems designed to manage it.

At the Gartner IT Symposium/Xpo this week, the analyst firm offered both its top 10 strategic technology trends for 2027 and its top 10 strategic predictions for 2027 and both lists shared some common themes: AI is making software faster to create and work easier to automate, while making costs, security, and accountability more difficult to govern.

The two lists are distinct, but I've synthesized them into a set of insights to watch for 2027:

• AI's capabilities are outpacing its controls: While AI is letting employees hand off more work to machines, it's also forcing leaders to rethink how they control costs, grant access, and decide who's responsible when things go wrong.
• More autonomy needs better accountability: The systems for managing AI need to catch up with its growing autonomy. By 2028, 25% of enterprise security breaches will trace back to AI agents with mismanaged credentials, Gartner predicts. Honestly, that number seems conservative.
• Disposable software will change the enterprise: AI makes software far easier to create. Gartner predicts that by 2029, 80% of all new applications will be used for less than a year and made to be intentionally disposable. Still, disposable applications don't make the underlying data, integrations, or security disposable.
• Better context becomes a business advantage: Even the most powerful model still needs to understand how your organization works to be effective. Organizing your enterprise knowledge so AI can use it will become as consequential as choosing the right model. By 2027, companies that prioritize making their data AI-ready will increase agentic accuracy by up to 80% and reduce costs by up to 60%, gartner predicts.
• AI spending becomes a security issue: Gartner warned that lower price per token does not guarantee a better business outcome. Companies need to focus on the cost to finish useful work, including the retries and mistakes the models make along the way. In fact, Gartner warned that attackers could use this against companies, warning against "cost exhaustion" attacks that drive excessive AI consumption to run up your bill. Gartner predicts that 80% of companies with public-facing AI will experience such an attack by 2030.

Nevertheless, Gartner analyst Daryl Plummer in his presentation on the 2027 predictions at the event, warned, "Your worst action is when you focus strictly on cost reduction. Don't do that. Cost reduction is the denominator. Value is the numerator. You have to worry about both of them to make the equation go the direction that you want."

Plummer also dealt with the elephant in the room: the impact of AI on jobs. He told the crowd full of executives and directors, "Don't think 'replace workers.' Think 'augment and extend.' That's the better way to go."

Our Deeper View

The organizations that will benefit the most from AI will be the ones that can clearly explain what AI is doing and why, and exactly how the outcomes justify the costs. While that should sound obvious, there's been so much emphasis on AI adoption for the past few years that many enterprises have kicked the can down the road on ROI. Gartner believes that period is over, and organizations have to get more disciplined and more systematic about AI transparency, accountability, and governance. As I mentioned in our report on Gartner's surveys of executives on AI, only 11% of CFOs said they are seeing clear returns from AI and only 13% of CIOs say their organizations have seen transformational value from AI. These numbers are going to have to rise for stakeholders to continue to believe in AI and keep funding investment. For its part, Gartner's predictions offered actionable insights and mental models for enterprises to adopt to get this moving in a better direction.