December 1, 2025
December 1, 2025
Today, we’re spotlighting three urgent themes: the imperative for organizations to move from AI hype to practical business value, the growing necessity for robust governance and literacy as AI adoption accelerates and the critical need for adaptive leadership to maximize technology investments. You’ll find targeted, actionable guidance for closing skill gaps, driving responsible innovation and securing competitive advantage as AI and digital transformation reshape every function.
The full insights are available only to clients with certain subscriptions. Gartner’s 2,500+ business and technology experts serve C-Level leaders and their teams across the business. To work with them, explore becoming a Gartner client.
What it’s about: This insights report explains how organizations can define and execute an AI-first strategy to capture transformative opportunities and avoid falling behind.
Why it matters now: The gap between AI hype and real business value is widening, and slow movers risk missed investments, stalled innovation and lost market share.
What to do next: Set a clear, strategic AI-first direction and align executive leadership to accelerate adoption and unlock measurable value.
What it’s about: This guide outlines decisive actions CIOs can take to cut real IT costs, focusing on SaaS and IaaS expenses rather than accounting adjustments.
Why it matters now: One-time, targeted reductions protect morale and productivity while delivering meaningful financial impact in a climate of budget pressure.
What to do next: Prioritize genuine cost-saving initiatives and avoid repeated small cuts to maintain team effectiveness and financial health.
What it’s about: This guide details how AI governance platforms help leaders centralize trust, risk and security controls while automating approvals for new AI use cases.
Why it matters now: Streamlined governance is essential as organizations scale AI, ensuring compliance, trust and operational efficiency.
What to do next: Evaluate and implement AI governance platforms to strengthen oversight and accelerate responsible AI adoption.
What it’s about: This guide helps CISOs navigate GenAI initiatives by demanding rigorous cybersecurity benchmarks and realistic performance standards.
Why it matters now: As AI hype peaks, GenAI projects face increased scrutiny and risk being dismissed as marketing-driven rather than secure and effective.
What to do next: Apply the same cybersecurity priorities to GenAI as to other digital infrastructure, and communicate realistic expectations to business leaders.
What it’s about: This guide presents seven critical factors for assessing SAP’s AI agents, helping leaders avoid vendor lock-in and optimize investments.
Why it matters now: With SAP’s agentic AI strategy evolving, organizations must evaluate long-term fit and cost implications before committing.
What to do next: Use the seven-factor framework to assess strategic fit and operational feasibility for SAP AI agents.
What it’s about: This insights report explains the impact of VMware Cloud Foundation 9.0 on both traditional VMware customers and those building private clouds.
Why it matters now: VCF 9.0 introduces higher costs and limited benefits for most VMware users, while offering advantages to private cloud builders.
What to do next: Assess your organization’s infrastructure needs and follow tailored guidance for maximizing value with or without VCF 9.0.
What it’s about: This guide shows how adaptive program governance drives faster strategic decisions and greater operational agility.
Why it matters now: 78% of executives now prioritize quick decision making, making decentralized, iterative governance essential for competitive speed.
What to do next: Implement adaptive governance frameworks to enable high-velocity decisions and improve time to market.
What it’s about: This insights report exposes five key pitfalls in deploying AI multiagent systems (MAS), from technical barriers to economic inefficiencies.
Why it matters now: Vendor claims are outpacing real capabilities, risking wasted investment and operational setbacks for engineering teams.
What to do next: Critically evaluate MAS platforms and focus on incremental, reliable deployments rather than chasing hype.
What it’s about: This insights report identifies barriers to analytics adoption among auditors and offers solutions to close gaps.
Why it matters now: Only 33% of CAEs provide clear analytics guidelines, and just 24% of auditors feel safe to experiment, limiting impact.
What to do next: Establish clear analytics procedures and foster a safe environment for experimentation to drive adoption.
What it’s about: These insights empower general counsel to drive reflexive risk management behaviors and systems across the business.
Why it matters now: Fast-moving, interconnected risks demand organizations respond quickly and thoroughly to protect value.
What to do next: Champion systems and practices that enable risk owners to act autonomously and effectively.
What it’s about: This guide empowers service leaders to reshape their organization’s reputation and relevance in the GenAI era.
Why it matters now: GenAI is redefining service roles, and leaders must act now to command respect and drive business growth.
What to do next: Leverage customer insights and build alliances to expand the service function’s impact.
What it’s about: This roadmap shows CFOs how to lead finance teams into a future dominated by AI agents, conversational interfaces and enterprisewide forecasting.
Why it matters now: Only 14% of organizations have governance for true AI enablement, and delay risks falling behind frontier finance teams already realizing major gains.
What to do next: Launch productive pilots, unify data and redesign roles to secure competitive advantage and accelerate AI adoption.
What it’s about: This guide helps HR leaders identify and prioritize the most impactful AI use cases amid market hype.
Why it matters now: Accelerating AI adoption can transform HR, but success depends on focusing investments where they deliver real value.
What to do next: Use the assessment to select and prioritize AI initiatives that drive HR transformation.
What it’s about: This guide shows communications teams how to move beyond GenAI experimentation to full integration.
Why it matters now: Without clear direction, GenAI pilots risk wasted resources and disengaged employees.
What to do next: Develop a structured GenAI integration plan to maximize value and team engagement.
What it’s about: This insights report explains how agentic AI enables marketing teams to deliver personalized, adaptive customer experiences.
Why it matters now: Gartner saw a 750% increase in AI-agent-related inquiries in late 2024, signaling rapid adoption and strategic importance.
What to do next: Assess your organization’s readiness and invest in AI agent capabilities to enhance marketing impact.
What it’s about: This insights report explores the mixed reality of AI in sales, balancing productivity gains with hype fatigue and new risks.
Why it matters now: Billions are invested in AI, but many pilots fail to deliver, creating urgency for leaders to separate value from hype.
What to do next: Focus on proven AI initiatives that enhance sales productivity and customer engagement, while managing risks.
What it’s about: This guide emphasizes the need for procurement teams to master both data and logic frameworks to succeed with AI.
Why it matters now: Implementation success varies widely, and comprehensive AI literacy is key to unlocking procurement value.
What to do next: Invest in AI literacy programs to build foundational skills and drive successful procurement initiatives.
What it’s about: This guide clarifies the limits of supply chain automation and the value of decision augmentation with AI.
Why it matters now: Overinvesting in automation can introduce risk; augmentation offers safer, more effective ways to enhance supply chain decisions.
What to do next: Focus AI investments on decision augmentation to improve supply chain resilience and avoid wasted spend.
What it’s about: This guide shows how digital literacy programs close skills gaps and boost ROI on R&D digital initiatives.
Why it matters now: Pressure to do more with less is burning out teams and undermining transformation success.
What to do next: Launch targeted digital skills programs to support R&D transformation and increase productivity.
What it’s about: This guide explains how product leaders can leverage new U.S. federal AI policies to strengthen their tech stack and partnerships.
Why it matters now: Looser regulations and infrastructure innovation are opening new opportunities for product differentiation and market leadership.
What to do next: Transform your product strategy and build strategic alliances to capitalize on America’s AI momentum.
What it’s about: This insights report explores how vibe coding accelerates application prototyping and reshapes enterprise software development.
Why it matters now: Despite some failures, vibe coding offers a path to faster innovation and new business models in the competitive AI landscape.
What to do next: Experiment with vibe coding in pilot projects to assess its impact and manage associated risks.
What it’s about: This insights report analyzes how large-scale intelligence platforms will disrupt high-tech revenue streams and business models.
Why it matters now: Trillions in AI infrastructure investments demand equally massive revenue, forcing industry-wide transformation.
What to do next: Reevaluate your business model and prepare for platform-driven disruption in the tech sector.
What it’s about: This guide highlights the rapid expansion of Earth intelligence from government to private sector, creating new revenue streams.
Why it matters now: Earth intelligence is set to transform every industry, and early adopters can gain significant competitive advantage.
What to do next: Integrate Earth intelligence capabilities into service offerings to drive growth and differentiation.
Drive stronger performance on your mission-critical priorities.