- McKinseys 2025 outlook highlights 13 frontier trends, with agentic AI rapidly rising as autonomous workflow systems gain attention.
- In 2024, agentic AI drew about $1.1B in equity investment and job postings jumped 985% YoY, while overall AI reached $124.3B and energy & sustainability led funding at $223.2B.
- Most companies remain in pilots (only ~12% scaled agentic AI across multiple functions), making execution, operating-model change, and ROI proof the main hurdles.
- Scaling is constrained by compute and energy needs, semiconductor and supply-chain pressures, and growing regulatory and digital-trust requirements that vary by region.
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The McKinsey “Technology Trends Outlook 2025” outlines 13 frontier technology trends, of which agentic AI has become especially prominent. While overall AI continues to dominate both interest (news, search queries) and innovation (patents, research publications), agentic AI — systems that can plan and execute complex workflows autonomously — has shot up from near-zero to becoming among the fastest-growing trends. In 2024 alone, equity investment in this area was ~$1.1 billion, and job postings surged 985% compared to the prior year.
Other major trends are also seeing significant movements. Equity investment in artificial intelligence overall rose to $124.3 billion in 2024; energy and sustainability tech saw $223.2 billion in investment, making it the top-funded trend despite a slight drop in hiring. Application-specific semiconductors, cloud & edge computing, and digital trust & cybersecurity also remain highly funded, though adoption levels vary.
Despite strong financial backing, many organizations are still stuck in experimentation and pilot phases for agentic AI and other frontier technologies. For example, agentic AI’s adoption rate is modest: many pilots but very few scaled deployments. From McKinsey’s surveys, only about 12 percent of enterprises have scaled agentic AI across several functions, though over 80 percent are running pilots or preparing for scale soon.
Scaling brings its own challenges: increased demand for computing power (leading to infrastructure strain and energy consumption concerns), supply chain issues especially around semiconductors, regulatory friction including data sovereignty and cybersecurity, plus the need for governance frameworks and workforce readiness. Companies embracing agentic AI are not just adopting tools but redesigning workflows, roles, and operating models.
Strategically, companies that act early not only gain technology advantage but also shape standards. Regional competition is intensifying: governments seek tech sovereignty, invest in local chip fabs, and regulate AI deployment. Digital trust — encompassing ethical AI, security, privacy — is no longer a “nice-to-have” but a competitive enabler, with regulatory risk increasingly material.
Open questions remain: what will be the true ROI from agentic AI, particularly when factoring in cost of infrastructure and change management? How soon will adoption shift from pilot to scale in non-tech industries? Which regulatory frameworks will dominate, especially for global businesses? And how will energy and environmental constraints limit or reshape the delivery of compute? These are uncertain, but critical for leaders to monitor and influence.
Supporting Notes
- Agentic AI pulled in about $1.1 billion in equity investment in 2024, with job postings growing +985% YoY.
- AI overall saw $124.3 billion in equity investment in 2024, with job postings up 35% YoY.
- Future of energy & sustainability technologies attracted $223.2 billion in equity investment in 2024; however, job postings declined 6% YoY.
- Cloud and edge computing saw $80.8 billion in equity investment in 2024; job postings were up just 2% YoY, signaling modest hiring despite investment.
- Survey data shows roughly 12% of enterprises have scaled agentic AI across multiple functions, while over 80% report running pilots or planning for scale.
- Companies that have evolved beyond early tests and adopted agentic AI broadly are reporting efficiency gains, reshaped workflow models, shifted talent requirements, and increased need for governance, compliance, and infrastructure.