Gartner expects autonomous AI agents, physical AI systems and new approaches to managing AI costs and accountability to reshape business and technology operations through the end of the decade. The research firm’s strategic predictions for 2027 and beyond focus on the spread of autonomous and physical systems, the relationship between AI costs and business value, and emerging risks associated with large-scale AI adoption.
Gartner predicts that more than 10 billion autonomous agents created by individuals, companies and governments will be interacting with public services by the end of 2030. Agentic AI could allow software to identify opportunities, determine eligibility and submit applications, claims and other requests with limited human involvement, increasing transaction volumes for government systems.
The company said governments will need stronger identity, verification and accountability mechanisms as AI-mediated interactions increase. It also expects public-sector organisations to modernise digital infrastructure to accommodate higher volumes of automated requests.
Physical AI is another area Gartner expects to expand. By 2030, it forecasts that 80% of front-line workers employed by international companies will receive assistance from physical AI systems. These systems include robots, drones, autonomous vehicles and other technologies capable of sensing and interacting with physical environments.
Gartner said such technologies are already being used to automate repetitive or hazardous work and collect operational information. Wider deployment would require organisations to develop governance frameworks, supporting platforms and workforce skills for operating physical AI systems.
Cybersecurity and Software Development
The expansion of public-facing AI could also introduce new cybersecurity and financial risks. Gartner predicts that by 2030, 80% of organisations operating public-facing AI will have experienced a “cost exhaustion attack,” in which malicious actors deliberately generate excessive AI usage to raise an organisation’s operating costs.
The firm said token consumption and other AI usage patterns could consequently become security as well as financial management considerations. Organisations may need controls capable of identifying unusual consumption and limiting excessive expenditure across AI systems.
AI-assisted software development is also expected to shorten the lifespan of some business applications. Gartner forecasts that 80% of new applications will be intentionally disposable by 2029, meaning they will be designed for less than a year of use.
Employees could increasingly build temporary applications for specific business requirements as AI reduces the effort required for software development. Gartner said this could create governance, compliance, security and records-management issues, particularly when temporary applications handle sensitive information or influence business decisions.
Energy and Insurance
Rising electricity consumption associated with AI and data centres could meanwhile change the role of large companies in energy markets. Gartner predicts that by 2030, Global 2000 companies will collectively own $10 trillion in energy assets and could sell electricity to grids and AI data centres.
Companies investing in generation, storage and energy-management infrastructure could therefore operate as both electricity consumers and providers. Gartner expects this shift to increase demand for platforms that coordinate energy production, storage and consumption alongside operational data.
Insurance companies could also play a larger role in determining how organisations govern AI. Gartner forecasts that by 2030 insurers will exert greater influence over AI governance than regulators through underwriting requirements for AI liability coverage. Companies seeking lower insurance costs could face requirements to demonstrate technical controls, oversight and risk-management practices.
AI Innovation and Cost Management
Competitive pressures are expected to affect how established companies develop AI products and services. Gartner predicts that by 2029, 25% of Global 500 companies will continuously develop componentised, AI-powered offerings rather than relying on strategies based on following competitors after products reach the market.
Managing the economics of AI deployment is another theme in Gartner’s forecasts. By 2029, the firm expects 60% of organisations deploying AI to have a dedicated function responsible for connecting the technology’s total cost with the value or profit it generates.
The growth of agentic systems could make that task more complicated because AI consumption can vary according to the number and complexity of tasks performed. Gartner said organisations will increasingly need to connect token consumption with business metrics while applying quotas, monitoring and other governance controls.
By 2028, Gartner also expects 60% of Global 500 companies to embed AI financial operations controls directly into inference processes. This would shift AI cost management from retrospective reporting towards controls capable of monitoring and adjusting expenditure as AI systems operate.
Such systems could measure factors including cost per task and token efficiency, supported by telemetry within the inference process. Gartner expects these controls to become part of AI platforms and applications as spending on the technology increases.
AI Accountability and Governance
Accountability for AI systems could also expand the responsibilities of senior technology executives. Gartner predicts that by 2030, 80% of Global 500 companies will contractually designate their chief information officer or chief AI officer as an “Evidence Custodian” responsible for AI accountability.
The role would involve maintaining evidence about AI actions and ensuring governance controls are applied across business processes. Gartner said organisations will need digital evidence-management capabilities and clearly assigned responsibility as AI becomes more deeply involved in operational and decision-making systems.
“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,” said Daryl Plummer, Distinguished VP Analyst and Gartner Fellow. “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.”
