It seems like every other business is using AI. From machine learning models that forecast marketing trends to chatbots that effortlessly solve customer queries—it appears that AI adoption is on the rise.
But how true is this really?
While there’s plenty of speculation and ample anecdotal evidence of AI adoption, there’s a lack of data on how many businesses are effectively adopting artificial intelligence, how they’re using it, and whether we can expect future growth.
To shed light on the matter and understand how businesses are managing AI adoption, we surveyed over 200 tech companies across the US, UK, and EEA. In this article, we guide you through their answers.
Here’s a deep dive into the AI adoption trends that defined 2024, themes to look out for in 2025, and how real businesses are navigating the challenges of AI adoption, including calculating its ROI.
Buckle up.
What is AI adoption?
AI adoption is the process of integrating artificial intelligence into business operations, products, or services, and involves using a range of AI products and systems to support workflows—from streamlining bloated tasks to strategic decision-making.
It can range from small-scale experiments to complete integration into core business functions, depending on the organization’s scope, pace, and desired outcomes.
What are the business benefits of adopting AI?
- Operational efficiency: AI automates repetitive tasks like data entry, and administration, streamlining bloated workflows and helping employees finish their work sooner. For example, finance AI tools can help capture invoices quickly, eliminating tedious data entry.
- Enhanced decision-making and forecasting: Models can quickly analyze vast amounts of data that give stakeholders insights to help them make informed decisions quickly.
- Better customer experience: AI-powered chatbots can provide 24/7 customer support and answer queries to improve customer satisfaction. Other AI SaaS tools can also analyze customer patterns and trends to help deliver personalized products and experiences.
- Cost-effectiveness: With AI automating routine tasks, businesses can cut costs on manual labor, hiring, and training—especially for repetitive jobs and workflows.
How are businesses using AI?
In January 2023, ChatGPT took center stage with exponential adoption growth and 33x more usage than its closest AI competitor. However, this usage growth has slowed considerably in the last year. Instead, we’re seeing more adoption growth with tools like Claude and Perplexity at 182%.
While adoption growth for ChatGPT has slowed down, it remains the most-used AI tool in organizations. That being said, it’s still far from taking the top spot in business tech stacks when it comes to usage. While it may have been adopted in more companies than HubSpot, the famous CRM sees 9 times more use than the AI poster child. ChatGPT also lags behind other SaaS tools like Figma, GitHub, and Notion.
Another crucial clue for unraveling how businesses use AI is by looking at spending in 2024:
- ChatGPT has experienced a flattened spending of 11%: Slower growth can be explained through its quick market saturation.
- OpenAI has seen a slower spending growth of 38%: Which is unexpected, considering its broad use cases.
- The CRM tool, Clay, has seen a spending growth of 600%: An AI tool that sources accounts, enriches data, and automates outreach—giving us a clue on some of the use cases for AI.
Businesses are also using generative AI now more than ever before. According to McKinsey, organizations of all sizes have been implementing gen AI into their sales, marketing, product and service development, and IT functions. Respondents further noted the specific tasks where generative AI was the most useful.
These include:
- In marketing and sales: some text
- Content support for marketing strategy (16% of respondents)
- Personalized marketing (15% of respondents)
- Sales lead identification and prioritization (8% of respondents)
- In product and service development:
- Design development (10% of respondents)
- Scientific literature and research review (6% of respondents)
- Accelerated simulation and testing (6% of respondents)
- IT: some text
- IT help desk and chatbot (7% of respondents)
- Data management (7% of respondents)
- IT helpdesk AI assistant (6& of respondents)
Rachel Whitehead, VP of Marketing at ChartMogul emphasizes the wide range of uses cases for AI in daily workflows:
“Initially, my team was using AI to enhance writing and speed up editing. Now, we use AI every day for brainstorming, summarizing, transcribing, researching, and automating workflows. I’ve never seen such a fast expansion of use cases.”
AI Adoption Rates in Small, Medium, and Large Businesses
Let’s look at AI adoption rate across different business types:
- Out of the 200 small and medium-sized businesses that Cledara surveyed, 79% of them regularly use or experiment with AI.
- Another report states that 42% of enterprise businesses surveyed have implemented AI models into their workflows.
- McKinsey highlights a giant leap in AI adoption rates from 60% to 72% after surveying global businesses
How Do Businesses Measure the ROI of AI Adoption?
Short answer: it depends.
AI tools are relatively new. Experimentation, uncertain market dynamics, shifting adoption rates, and uncertain timing of benefits all make it difficult to define return on investment (ROI)—let alone assess it.
Where do companies begin?
The first step is to differentiate between non-financial and financial impact. For example, automation increases efficiency by reducing the time taken to complete manual tasks. This is a direct financial benefit that you can calculate.
If a task that took 10 hours to complete now only takes two with the help of AI, you can calculate cost savings by multiplying the saved hours by the employee’s hourly wage. This directly impacts a company’s bottom line.
However, that also frees up time and bandwidth for employees to focus on creativity, strategy, and innovation—all of which are more difficult to track. While this does give you a long-term, competitive advantage, they don’t have immediate, measurable financial outcomes.
Lucas Botzen, Founder and CEO at Rivermate, shares how he looks at direct and indirect impacts, and also considers customer experience an important consideration when looking at the ROI of AI adoption:
“At Rivermate, several key performance indicators are of interest to us: time usage, reduction in the error rate, cost savings due to automation of hitherto manual tasks. We track the effect it has on employee satisfaction, since easier workflows allow our workforce to concentrate on high-level, value-added tasks and not mere repetition. “
Of course, how you measure ROI will differ depending on your organization, whether you’re using AI in B2B or B2C, and the scope of its implementation. While some businesses can directly link efficiency KPIs to adopting artificial intelligence, others might have difficulty doing so.
Guy Melamed, CFO of software security provider Varonis, stated for SAP Concur’s “Solving the ROI puzzle: How to measure and maximize AI returns” gives insight into the process:
“We stick to clearly measurable productivity gains, such as lines of code, journal entries or expense reimbursement checks completed by AI. This has led us to emphasize AI projects that reduce tedious tasks, help employees use their time better, and gain job satisfaction and engagement. It doesn’t necessarily need to create a large cost saving; just be at least cost neutral.”
What AI Adoption Challenges Do Businesses Face?
While it yields tons of benefits, adopting AI into your business is no simple task. Small, medium, and large businesses regularly face a swathe of challenges for fruitful implementation, some of which we don’t have complete solutions for (yet!).
Some of these main challenges include:
- Data quality and management: Generative AI outputs are only as useful as the data you feed them. Businesses often struggle with structuring and cleaning quality data sets to get the best answers possible from AI.
- Integration issues: Businesses often have issues seamlessly integrating AI into their IT infrastructures and workflows. This is especially an issue with businesses that use legacy systems, outdated software that lacks the compatibility to support AI systems.
- Operational risk: Businesses can adopt too much, too fast—putting workflows, operations, and project goals at risk if the model has bugs or inaccuracies. Integrating these technologies and processes into your workflow needs to be sustainably manageable.
- Organizational resistance: Many employees may resist AI adoption for fear of job displacement, slowing down the adoption process. These employees hinder the adoption process by refusing to adjust to new processes.
Lucas shares some of the challenges that the Rivermate team faced when adopting AI into their workflows:
“Development faced large initial setup challenges to integrate into already existing systems, and the learning curve for such AI-driven workflows is steep among less familiar team members. It's been important to us to keep training and change management running simultaneously to make things seamless.”
The Future of AI Adoption: Find Out More
Almost three years after they burst onto the business scene, companies continue to adopt AI solutions into their operations. From streamlining bloated workflows to forecasting future marketing trends—AI is doing it all.
While the adoption of AI remained high throughout 2024, its perceived value and businesses’ willingness to spend on these tools lags behind. It remains to be seen whether this will pick up in 2025, with 42% of businesses not intending to allocate additional funds to AI in the coming year.
Compared to popular SaaS tools like Google Workspace, HubSpot, and Microsoft, monthly AI churn rates are significantly higher at 3.25%. However, this might signify experimentation, rather than long-term dissatisfaction. While businesses see the potential in AI, they’re still uncertain on how to realize it and effectively measure ROI.
These stats put AI adoption at a major crossroads.
Cledara’s AI in 2025: The Data Behind The Hype report covers the key trends, challenges, and opportunities businesses face as they adopt AI into their workflows. Download the report to find out more about the trends defining AI adoption in small and medium-sized businesses.
For now, we’ll leave you with ChatGPT’s thoughts on the future of AI adoption in SMBs:
“AI adoption in small and medium-sized businesses (SMBs) will drive growth by improving customer experience, automating tasks, and enabling data-driven decision-making. As AI becomes more accessible and affordable, SMBs will enhance productivity, innovate, and compete more effectively.
While challenges like data privacy and skill gaps remain, AI’s potential to streamline operations and reduce costs will be transformative for businesses of all sizes.”
Our thoughts?
Read the report to find out.
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