KPMG survey: AI agents will reshape tech teams by 2027

What changed: A new global KPMG report summarized by Moneycontrol finds that 92% of 2,500 technology executives expect AI agent management to become an essential leadership skill within five years and 88% say their organizations are already investing in agentic AI technologies. Digital assistants are projected to account for 36% of core technology teams by 2027, up from 28% in 2025, signaling a rapid shift toward human–AI collaboration in day‑to‑day tech work.

Why it matters: Technology leaders need to treat agent management as a core capability, not a side experiment, and start defining roles, skills, and responsibilities around supervising AI agents. This shift also implies restructuring teams and workflows so that agents handle repeatable tasks while humans focus on coordination, oversight, and complex decisions.

Try/watch: Start a small “agent management” pilot team that owns design, governance, and performance metrics for agents, and track how much real work moves from people to AI over the next 12–24 months.

Agentic commerce: AI shopping agents are buying now

What changed: A new 2026 “agentic commerce readiness” checklist argues that AI shopping agents are already placing real orders, yet most online store catalogs remain effectively invisible to them because of poor data and integration. The article cites Adobe Analytics data showing AI‑sourced traffic to U.S. retail sites grew 393% year over year in Q1 2026 and converted 42% better than organic traffic, while today only about 3% of transactions involve an AI agent even though 33% of consumers expect at least 10% of their purchases to be AI‑driven within a year.

Why it matters: Merchants that structure product feeds, policies, and checkout flows so agents can read, qualify, and complete purchases will capture disproportionately valuable traffic as agents become a common buying interface. Ignoring this channel risks losing high‑intent customers to competitors whose stores are machine‑readable and frictionless for agents.

Try/watch: Score your store against the six readiness pillars described—product feed, structured data, protocol integration, machine‑readable policies, trust signals, and AI citation—and prioritize fixes where agents are most likely to stall today.

Gartner trend: decision governance and sovereign AI for agents

What changed: A Connected World analysis of Gartner’s 2026 data and analytics trends highlights sovereign AI, decision governance for AI agents, and AI governance platforms as top priorities as organizations adopt more autonomous systems. Gartner predicts that by 2029, explicitly modeled and governed business decisions will be five times more trusted and 80% faster than ungoverned decisions, underscoring the value of transparent, auditable agent decision-making.

Why it matters: As agents take on strategic and operational tasks, poorly governed decisions become a major legal, operational, and reputational risk. Investing in decision governance—clear policies, audit trails, and control over where data and models run—can turn agent autonomy from a liability into a competitive advantage.

Try/watch: Map your highest-value agent use cases, then design explicit decision policies and audit requirements for each before scaling, including who can override an agent’s decision and how evidence must be logged for regulators or customers.