Technology leaders are more than a little fond of dragging out their crystal balls and scrying into the future as the year ends, but analysts at market research firm Gartner have stolen a march on their peers and have already outlined their top 10 strategic predictions for 2027 “and beyond”.
And, according to distinguished VP analyst and Gartner Fellow Daryl Plummer, it’s going to be a wild ride.
“Many of the systems we take for granted today, from public services to software, energy and workforce models, will be fundamentally transformed by AI over the next decade,” Plummer said at today’s Gartner IT Symposium/Xpo on Australia’s Gold Coast.
“The most successful organisations will be those that balance innovation with responsibility, building the capabilities needed to manage both the opportunities and the unintended consequences of an AI-driven world."
Top strategic predictions for 2027 and beyond
1. By the end of 2030, more than 10 billion autonomous agents will clog public services.
Agentic AI will flood governments with applications, claims, and transactions as agents identify opportunities, check eligibility, and submit requests for users. Gartner recommends modernising digital infrastructure, strengthening identity and verification, and preparing for higher volumes of AI-mediated interactions.
2. By 2030, 80 per cent of front-line workers employed by international companies will be assisted by physical AI systems.
Robots, drones, and autonomous vehicles will increasingly handle repetitive and hazardous work while improving safety and operational insight. Gartner recommends scalable platforms, robust governance, and investment in the skills needed to manage physical AI safely.
3. By 2030, 80 per cent of organisations with public-facing AI will have experienced a cost exhaustion attack creating excessive AI cost.
Attackers will deliberately drive AI usage and token consumption to inflate costs. Gartner recommends treating token spend as a cyber security indicator, deploying cost-focused controls and monitoring AI systems for abnormal usage.
4. By 2029, 80 per cent of new applications will be intentionally disposable – used for less than one year.
AI will make it easy for employees to build short-lived applications, creating fresh governance, security, compliance, and records-management risks. Gartner recommends risk-based governance, automated application registries and updated retention policies covering AI-generated applications and agents.
5. By 2030, US$10 trillion in enterprise-owned energy will make Global 2000 firms unexpected power providers.
Rising demand for AI and data centres will push enterprises into energy generation, storage, and trading. Gartner recommends energy-management platforms, integrated energy and operational data, and governance and infrastructure to participate in emerging energy markets.
6. By 2030, insurers – not regulators – will drive AI governance, with strict underwriting standards for AI liability insurance required to reduce costs.
Insurers will increasingly demand stronger AI oversight, risk management and technical controls. Gartner recommends embedding governance into AI systems, testing controls in real environments, and establishing runtime oversight.
7. By 2029, 25 per cent of the Global 500 will continuously innovate componentised AI-powered offerings, creating a competitive moat that obsoletes fast follower strategies.
AI-native competitors will raise the pressure on established companies to innovate or lose market share. Gartner recommends prioritising AI-powered customer innovation while strengthening data, analytics and workforce capabilities.
8. By 2029, 60 per cent of organisations deploying AI will establish a dedicated function responsible for mapping AI total cost to value or profit.
As agentic AI drives token consumption and costs higher, organisations will need to prove that AI spending delivers business value. Gartner recommends linking token usage to value metrics and introducing clear governance, quotas, and monitoring.
9. By 2028, 60 per cent of Global 500 companies will embed AI FinOps control at inference, shifting cost governance from reactive reporting to real-time optimisation.
AI spending will move from retrospective reporting to real-time control as organisations measure cost per task and token efficiency. Gartner recommends runtime cost controls, inference-path telemetry, and AI cost governance across platforms and applications.
10. By 2030, 80 per cent of the Global 500 will contractually make their CIO (or CAIO) the ‘Evidence Custodian’ for AI accountability.
Technology leaders will take greater responsibility for proving how AI systems act and make decisions. Gartner recommends assessing digital evidence capabilities and assigning clear accountability for AI actions.
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