Exploring the next phase of AI adoption in modern organizations
The next phase of AI adoption in modern organizations is focused on integrating the technology into everyday workflows, measuring results, and addressing the challenges of scaling its use across teams.
Nearly nine in ten organizations now report regular use of artificial intelligence in at least one business function, according to McKinsey's 2025 State of AI survey. Yet most remain in the early stages of expanding the technology across their operations.
That gap points to a new phase of AI adoption. Many organizations are no longer asking whether AI can be useful. They are trying to determine where it fits into everyday work and where it can produce meaningful results.
As AI becomes more common across business functions, attention is shifting from experimentation to practical use.
Why Are Businesses Moving Beyond AI Experiments?
For many organizations, the first wave of AI adoption focused on testing what the technology could do. Teams experimented with content creation, customer support tools, data analysis, and workflow automation. Some projects produced promising results, and others helped companies identify situations where AI was less useful than expected.
The conversation is now becoming more practical. Business leaders want to know whether a tool saves time, reduces repetitive work, or helps teams make better decisions. Companies are looking beyond small tests and focusing on uses that can support everyday work.
What Areas of Business Are Seeing the Greatest Impact From AI?
Artificial intelligence is being used in different ways across industries. Several business functions continue to attract the most attention.
Customer Service
Many organizations use AI in customer service to assist with routine customer questions, appointment scheduling, and support requests. This can help teams respond more quickly while leaving more complex situations to human employees.
Marketing and Content Operations
Marketing teams use AI to support content creation, audience research, campaign planning, and performance analysis. In many cases, the technology is helping teams complete tasks faster rather than replacing existing processes.
Revenue and Go-To-Market Operations
Sales and marketing teams are under growing pressure to make sense of large amounts of customer and market data. Organizations are increasingly exploring platforms such as GTM AI to help connect data, teams, and decisions across sales and marketing activities.
Workflow Automation
Administrative tasks remain a major area of interest. Organizations are exploring ways to automate activities such as data entry, document processing, scheduling, and reporting, allowing employees to focus on more valuable work.
AI Adoption Challenges Are Getting the Spotlight
Experimenting with enterprise AI is one thing. Expanding its use across an organization can be much more difficult.
Choosing a tool is only one part of the process. Teams also need reliable data, clear guidelines, employee training, and workflows that support the new technology. A tool may perform well during a pilot project yet encounter obstacles when introduced across multiple departments.
The next phase of adoption may depend less on access to AI tools and more on how effectively organizations incorporate them into everyday work.
The Age of Enterprise AI Is Here
Many organizations have already moved beyond experimenting with artificial intelligence. Attention is increasingly focused on finding useful applications, improving day-to-day work, and addressing the challenges that come with broader AI adoption.
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