The state of AI in 2025, McKinsey 2025 Report: Key Findings

A summary of McKinsey’s 2025 AI report, covering adoption trends, the rise of AI agents, and why high-performing companies see faster growth through workflow redesign and automation.

Why More Companies Are Turning to AI Agents and Why Those Who Do Are Seeing Greater Returns

A clear look at why AI agents are gaining momentum in 2025 and how early adopters are achieving higher efficiency, lower costs, and stronger customer experiences by redesigning workflows around automation.

1. AI Adoption Is Entering a New Phase

The conversation around artificial intelligence changed dramatically in 2025. For years, AI lived in an uncertain space between excitement and hesitation, with businesses unsure how to extract meaningful outcomes from early pilots. The newest McKinsey analysis signals a clear shift. AI is no longer a novelty or an experiment. It is becoming a core operational requirement. Nearly 88% percent of companies now use AI in at least one business function, a number that reflects complete mainstream adoption. Yet the majority still struggle to scale it. Many organizations run pilots, but very few turn those pilots into repeatable, business-wide impact. This bottleneck is exactly where AI agents begin to matter.

2. AI Agents Are Moving From Experiments to Scalable Operations

According to the report, 62% of organizations already use or experiment with AI agents, and nearly a quarter are scaling them across at least one function. This is not simply a rise in interest. It represents a meaningful transformation in how companies design work. AI agents automate multi-step tasks, interpret context, reference structured company data, make routing decisions, and follow real workflows rather than generating isolated responses. As a result, companies see measurable gains in speed, operational accuracy, and cost efficiency.

While early chatbots acted as conversation responders, AI agents act as workflow operators. They escalate cases, gather required information, update systems, and return results with consistency. This evolution explains why so many companies are beginning to integrate AI agents into customer service, knowledge management, sales operations, IT processes, and administrative tasks.

3. Why High Performers Are Pulling Ahead

A particularly important insight in the McKinsey analysis is the existence of a small but rapidly growing group of companies referred to as AI high performers. These organizations treat AI adoption as a strategic initiative. They deploy AI agents across multiple functions rather than isolating them to single teams. They invest significantly more in AI readiness, particularly in data quality, workflow redesign, and leadership involvement. High performers are more than three times as likely to pursue transformative AI use cases instead of incremental ones. They redesign processes rather than layering AI onto legacy workflows.

This is why the gap between high performers and the rest of the market is widening. Companies that integrate AI agents now are positioning themselves for compounding advantages, while late adopters risk falling behind not only in efficiency but in customer experience and product velocity.

4. What This Means for Customer Support and Service Operations

This research connects directly to what is happening in customer service. Support teams face a constant cycle of pressures: high volumes of repetitive tickets, growing customer expectations, global demand, and minimal tolerance for slow responses. Traditional chatbots can no longer satisfy these needs. They often deliver generic or unreliable answers, cannot follow logic, and require manual effort to maintain.

AI agents solve these limitations by using verified company information, interpreting full conversation context, following escalation rules, and operating inside existing helpdesk systems. They deliver reliable and measurable automation. Companies adopting agentic AI in support see reduced ticket volume, faster response times, improved accuracy, and lower cost per interaction. This reflects the same transformational pattern observed among high performers in the McKinsey report.

5. How CoSupport AI Fits Into the Shift Toward Agentic Automation

The way CoSupport AI approaches automation aligns closely with what the McKinsey report identifies as the winning strategy. Instead of layering a general-purpose AI on top of existing tools, CoSupport AI rebuilds workflows around accuracy, consistency, and automation. The platform uses company data, structured knowledge bases, and internal rules to drive AI agents that operate inside helpdesk systems, manage routing, follow escalation logic, and maintain traceability. This eliminates the reliability problems that prevent many organizations from scaling AI. It also supports the very behavior that defines high-performing organizations: workflow redesign and operational transformation.

Companies implementing CoSupport AI are not just improving response times. They are completely reshaping how work moves across their support operations, allowing their teams to focus on complex cases, relationship building, and revenue-driving tasks instead of repetitive administrative activity.

6. Visualizing the Business Value of AI Agents

The McKinsey report includes several powerful data points on how AI improves performance across innovation, customer satisfaction, operational cost, and revenue. These insights can be translated directly into visual elements that emphasize the financial value of AI agents.

Infographic placement suggestions:

• A chart showing impact categories: innovation, cost reduction, revenue acceleration, speed.
• A visualization of ROI accelerators among companies that have redesigned workflows with AI.
• A chart illustrating where AI agents are used most frequently by industry.

Each of these graphics strengthens the narrative that the companies deploying AI agents see better outcomes, higher productivity, and stronger competitive positioning.

7. The Future Will Belong to Companies That Act Now

The real message across the McKinsey analysis is clear. AI is no longer experimental. AI agents are becoming the operational standard. The businesses that adopt them early are already outperforming peers, and this advantage will continue to compound. Those who wait may find it difficult to match the speed, efficiency, and consistency of companies that redesign their workflows with AI at the center.

The companies that invest now will gain capabilities that fundamentally change how they operate. AI agents reduce friction, eliminate repetitive workload, accelerate customer responses, improve decision-making, and modernize entire business functions. The opportunity is immediate, practical, and measurable.