Gartner forecasts AI-driven changes in jobs, money & global rules

Gartner has identified its top predictions for information technology organisations and users for 2026 and beyond, focusing on developments in talent, sovereignty, and artificial intelligence risks.

Changing talent landscape

Daryl Plummer, Vice President, Distinguished Analyst, Gartner Fellow and Chief of AI Research for the Gartner High Tech Leaders and Providers practice, commented on the impact of technology on human behaviour. "The risks and opportunities of rapid technology change are increasingly affecting human behaviour and choices. To properly prepare for the future, CIOs and executive leaders should prioritise behavioural changes alongside technological changes as first-order priorities."

According to Gartner, generative AI (GenAI) and AI agents are set to provide the first significant competition to mainstream productivity tools in three decades by 2027, driving a projected USD $58 billion market change. As AI capabilities progress, vendors are expected to shift previously fee-based GenAI features to no-cost tiers, expanding access and generating new market entrants.

Gartner predicts that by 2027, 75% of hiring processes will incorporate certification and testing to assess candidates' proficiency with AI in the workplace. This is particularly relevant for roles involving substantial information handling and synthesis. Standardised assessments will support organisations in identifying AI skill gaps within their workforce. The increasing relevance of GenAI capabilities is expected to influence salary levels, leading candidates to seek formal demonstration of their AI skills as a competitive advantage in job markets.

AI and critical-thinking challenges

Another trend identified is the potential impact GenAI use may have on critical-thinking skills. Gartner forecasts that by 2026, 50% of global organisations will require 'AI-free' skills assessments as part of their recruitment strategies. These assessments will help employers distinguish between candidates capable of independent reasoning and those who are overly reliant on machine-generated outputs. This development is particularly pertinent in industries like finance, healthcare, and law, where cognitive ability and independent judgement are strategic priorities, resulting in increased hiring costs for sought-after skills. The report anticipates the growth of specialised platforms for evaluating human reasoning abilities.

"Enterprises that successfully integrate AI-free evaluation into their broader talent strategies will protect the 'human edge' in decision quality and adaptability, providing an advantage that will compound as GenAI reshapes the competitive landscape."

Regionalisation of AI platforms

Gartner also projects significant regional variation in the adoption and deployment of AI solutions. By 2027, 35% of countries are expected to use region-specific AI platforms with proprietary contextual data, prompted by regulatory requirements, linguistic differences, and cultural considerations. This development will complicate efforts by multinational companies to implement uniform AI systems globally, requiring partnerships with various platform providers.

Vendors will likely prioritise alliances with sovereign cloud providers and open-source models to comply with local demands. Those unable to demonstrate value tied to local context may lose competitive positioning, especially in industries with substantial regulatory requirements or cultural sensitivities.

AI in business processes and transactions

Gartner predicts that by 2028, companies using multiagent AI for at least 80% of customer-facing processes will have a competitive edge. Human involvement will remain necessary for managing complex interactions, while AI will increasingly handle routine requests. The firm also anticipates that organisations not investing in multiagent AI for customer relationship management risk lagging behind as customer expectations increase for swift, low-effort service experiences.

By 2028, Gartner expects 90% of business-to-business transactions will be intermediated by AI agents, representing over USD $15 trillion in B2B spend mediated through AI exchanges. This will involve new high-frequency, automated commercial models where operational data becomes critical in establishing digital trust and supporting composable, cloud-native product architectures.

Legal and regulatory implications

The expansion of AI also brings legal and compliance challenges. Gartner forecasts that by the end of 2026, legal claims involving 'death by AI'-wrongful death due to AI failures-will surpass 1,000 incidents. Organisations will respond to increased regulatory attention by enhancing safety measures and transparency, and some may even use their level of AI adoption, or lack thereof, as a differentiator in the marketplace to minimise litigation exposure.

Further, AI and decision governance failures will expose organisations to a range of legal and reputational risks depending on geography, as regulatory frameworks continue to diverge internationally.

Programmemable money and AI agents

By 2030, Gartner predicts that 22% of monetary transactions will be programmable, embedding terms and conditions for use to facilitate economic agency for AI agents. This shift is expected to support new business models via machine-to-machine commerce, automated negotiations, and data monetisation. Programmemable transactions are set to deliver efficiency and liquidity benefits across supply chains and the financial sector.

The growing presence of machine customers and AI agents with economic agency will lead to a demand for programmable financial infrastructure and the mainstream use of stablecoins, deposit tokens, and tokenised real-world assets. However, market growth will be restricted by variations in industry standards, a lack of interoperability, and potential security vulnerabilities, driving further regulatory intervention.

Cost control and regulation

Gartner estimates that agentic AI will reduce the cost-to-value gap for process-centric service contracts by at least half by 2027, as AI agents discover and apply hidden knowledge, enabling new forms of value creation and shifting innovation-based pricing models away from labour-centric calculations.

The forecast also suggests that fragmented AI regulations will soon cover half the world's economies. This development is expected to drive USD $5 billion of compliance investment by 2027, requiring technology leaders to continually update their understanding of laws and implement governance programmes with dedicated staff and technology capabilities to manage AI risks.