AI in Business: What Percentage of Companies Are Using AI?

Not long ago, AI lived on the peripheries of corporate strategy, tested in isolated pilots. 

In 2025, it has become the center of business operations, with IBM reporting that 42% of businesses have actively deployed AI, and 40% are experimenting across departments. 

A lot has changed in a decade, from AI tools being a concern to being a solution in corporate decision-making. Still, there are some challenges making it tricky to translate its adoption into measurable results. 

From fintech startups automating fraud detection to manufacturers deploying predictive maintenance, AI is powering decisions that directly shape revenue and efficiency. Yet, adoption is not translating evenly into measurable returns. Many executives still struggle to capture real enterprise value.

This article breaks down the percentage of businesses using AI in 2025 and discusses adoption by industry. It will help you make the transition from experimentation to impact in business.

What are the strategic takeaways and insights from trends of AI in business?

Below is an overview of the state of AI in business and what it means for you. 

• Treat AI as a core part of your business strategy. Executive sponsorship is critical to drive AI initiatives forward. Ensure there is C-suite or board-level oversight for AI projects and governance. Although 84% of global executives think responsible AI (RAI) should be a priority for top management, only 25% have fully developed RAI programs.
• Build an AI-capable workforce by upskilling employees and selectively hiring specialists. Given that 40% of enterprises cite insufficient AI expertise as a barrier, proactive talent development will help you stand out.
• Embrace governance, ethics, and change management: Implement an AI governance framework to ensure ethical, compliant, and transparent use of AI.  This will help maintain trust with customers, employees, and regulators. Involving legal and compliance teams early will help navigate any regulatory requirements. Concurrently, prepare your organization culturally and communicate clearly how AI will augment roles and bring new opportunities. Provide training and resources to help employees adapt to working with AI tools.
• Stay adaptive and continue investing: Monitor industry benchmarks and competitors’ AI advancements. If 92% of companies plan to increase AI spending in the next few years, falling behind is not an option. Be prepared to invest consistently in tools and people.

What percentage of businesses are using AI in their operations?

78% of companies worldwide use AI in at least one business function. 

This represents a significant increase from 20% in 2017, reflecting the pace of AI adoption over the past few years. Over 90% of all companies are either using or actively exploring AI today. 

Key insights based on current stats of AI in business: 

• AI is a long-term strategy. Businesses are not only experimenting with AI, they are investing in it for the long term. 92% of firms plan to increase their AI investment over the next three years.
• Enterprises have integrated AI in some form. IBM’s global index found roughly 42% of businesses had actively deployed AI by 2024, and many others were running pilots. 

AI is no longer an exception. It has become a norm in business across various geographies and sectors. 

What are the AI adoption trends by industry in 2025?

AI adoption in businesses varies in terms of degree and adoption. Below, we break down AI adoption trends and top use cases in key sectors to illustrate how each is leveraging AI in 2025.

AI in fintech businesses

An EY study shows that 85% of professionals use AI for increased speed, efficiency, and the opportunity for deeper data-driven insights. 

The key use cases involve: 

• Fraud detection and security: About 90% of financial institutions employ AI-driven systems to expedite fraud investigations and spot emerging threats.
• Customer service chatbots: 37.4% of the U.S. population is estimated to have interacted with a bank’s chatbot in 2022. This is expected to reach 40.8% in 2026.
• Credit risk and underwriting: In a survey, 60% of GenAI usage was found to be in portfolio monitoring. Over 40% of respondents were using AI in the credit application process. 

Despite different gains, many executives acknowledge that scaling up genAI applications in credit risk will be challenging. 75% of them see risk and governance as the most significant challenge. 

AI in manufacturing businesses

According to a whitepaper from the National Association of Manufacturers, manufacturing businesses are using AI for: 

• Reducing costs and improving operational efficiency, say 72% of respondents. 
• Improving operational visibility and responsiveness, say 51% of manufacturers. 
• Improving process optimization and control, say 41% of professionals.

Based on this, different corporate functions in manufacturing have started adopting AI, for example: 

However, legal, procurement, and sustainability functions see minimal AI adoption, close to 3% each. 

AI in retail businesses 

Many retailers are already using AI in some capacity. It’s helping them improve the customer experience while streamlining operations. Here’s an overview of how retail businesses make use of AI: 

• Store analytics and insights: Close to 53% of companies in retail use AI for insights like queue analytics and heat mapping. They are mostly in food and drinks, department stores, and grocery stores’ retail segments. 
• Personalized marketing and product recommendations: 47% companies are investing in using AI to deliver personalized recommendations. 28% use it for adaptive advertising and pricing. 
• Loss prevention and asset protection: 54% of C-suite executives in retail use AI in their asset protection strategies.
• Augmented reality experiences: 28% of retail companies are using AI to deliver augmented reality experiences to their customers, especially in cosmetics, beauty, and perfume segments.

AI in healthcare

Compared to other industries, healthcare is below average in terms of AI adoption as per the World Economic Forum. However, in many cases, AI technologies are helping doctors in detecting fractures and early signs of diseases. Here’s a summary of the most significant stats that reflect the healthcare AI adoption: 

• $9.33 billion was the annual private investment in AI in 2024 for the medical and healthcare sector. 
• A study in Yorkshire found that AI accurately predicted hospital transfers for patients 80% of the time.
• Only 29% of people in the UK would trust AI to offer basic healthcare. 

Doctors vs. AI

Interestingly, research published by JAMA Network Open compared diagnosis delivered by an individual physician, a doctor using an LLM tool, and only an LLM. Surprisingly, LLM scored 16 percentage points more than a doctor’s diagnosis in terms of accuracy. 

For a doctor and LLM duo, accuracy improvements were insignificant. Here, LLM + Doctor scored 76% while the doctor alone scored 74%. It seems LLMs aren’t helpful for doctors, but it’s also important to note that only 10% of doctors were experienced LLM users.

AI in SaaS

In the software-as-a-service (SaaS) and technology businesses, AI is increasingly becoming popular. Around 70% of companies incorporate some level of AI into their products, and a similar share of enterprises use it internally across various workflows. 

And it seems profitable. A notable 43% of equity-backed companies leveraging AI are either profitable or breaking even, compared to just 30% of those not utilizing AI. Interestingly, there is a trend in how companies are expecting the ROI from their AI investments. For example, Better Cloud’s State of SaaS report suggests that 34% of companies expect returns within a year. Another 32%, expect in one to two years. Some (25%) are patient and are expecting returns in two to four years.

AI in insurance 

The insurance industry, traditionally data-driven and risk-focused, is rapidly adopting AI to transform how insurers operate. Surveys show that nearly 90% of insurance executives identify AI as a top strategic priority for 2025.

While not all insurers have fully deployed AI yet, virtually all are somewhere on the adoption curve. Below, we cover the key use cases of AI in insurance. 

• Claims processing automation: 72% of insurance companies have cited improving the claims cycle as a top priority with AI. 
• Underwriting and risk assessment: 53% of insurance professionals are prioritizing speed to quote using AI. 

Despite the uplifted enthusiasm, only 22% of insurance companies have their AI solutions fully running in production. 

Exploring the rise of AI in businesses

There’s a lot of enthusiasm related to AI usage in every part of business. Some are expecting process improvements while others have their eyes on its efficiency gains. While all of it seems like a no-strings-attached situation, it’s not. 

Based on Harvard’s Working Knowledge article, there are three problems that companies face with AI: 

• Failing to develop internal AI talent
• Deploying AI without sufficient cybersecurity measures
• Investing in tools that can’t scale

Due to these, AI’s implementation isn’t as easy or rewarding as it looks. If AI is a part of your strategy, it’s advisable to plan for these challenges early and decide what you can accommodate. 

This will help you set more realistic expectations with AI implementation in a business. 

With this understanding, if you’re looking to build or onboard a new AI tool, check out the most popular AI tools on the market right now!