The big picture: By 2029, 60% of organizations will adopt smaller software engineering teams at scale, up from 15% in 2026. This signals a major shift in how teams are structured.
Why it matters: Leaders must prepare for rapid changes to engineering org design and hiring strategies. Skills and roles that matter today may not fit smaller, AI-augmented teams of the future.
The big picture: CX leaders are told to avoid an all-or-nothing approach and balance AI with human support. Managing employee skepticism and frontline morale is treated as core to the strategy, not a side effect.
Why it matters: Adoption depends on employees owning the technology rather than fearing it. Transparent communication about role changes is the lever leaders control.
The big picture: S&P Global is restructuring its Market Intelligence division around AI-native tools and workflows. The new operating model simplifies client interfaces and speeds the rollout of agentic applications, alongside executive leadership changes.
Why it matters: A data incumbent is redesigning how it delivers, not just what it sells. AI-native workflows are being embedded into the core platform rather than bolted on.
The big picture: As organizations accelerate AI adoption, CHROs need a more active role in assessing workforce-related costs tied to AI transformation. These costs are often overlooked in ROI calculations.
Why it matters: AI ROI is fragile when human costs are underestimated. Leaders who ignore workforce expenses will see inflated AI payback projections and misallocate resources.
The big picture: Demand for supply chain roles requiring AI skills has jumped 387% from early 2023 to early 2026. This growth far outpaces overall labor market expansion.
Why it matters: Supply chain functions are becoming a fierce battleground for AI talent. Leaders competing for these scarce skills will need to act quickly on hiring and retention or watch capabilities stall.
The big picture: CFOs must learn from frontier finance teams, which are furthest along in building AI-enabled decision support, digital talent, and new operating models. This shift will reshape enterprise decision-making by 2030.
Why it matters: Finance functions that move first on AI-enabled decision support will drive smarter, faster enterprise choices. CFOs who lag will watch competitors make better capital and strategic calls.