Why AI Adoption Is Failing To Deliver The Returns Businesses Expect

AI adoption is delivering mixed results for businesses, with clear evidence showing the gap between hype and measurable return. According to a recent MIT “State of AI in Business 2025” study, only about 5% of enterprise generative AI pilots achieve rapid revenue acceleration, while roughly 95% fail to deliver meaningful business impact. This sobering statistic underscores how many organizations are investing heavily without translating innovation into profit or productivity.

According to McKinsey’s State of AI in 2025 survey, while 88 % of organizations now use AI in at least one business function, only about one-third are scaling AI enterprise-wide, and just 39% report any measurable impact on earnings from AI adoption. This has created a reality in which executives are forced to reconsider assumptions about speed, scale, and strategy when it comes to artificial intelligence deployment.

Against this backdrop, understanding both the myths and practical strategies around AI adoption is critical. It is no longer sufficient to chase the latest tools without clear integration plans and measurable business outcomes. Leaders need insight into not just what AI can do, but how and where it delivers real value.

In this exclusive interview with the Cyber Security Speakers Agency, Brett Schklar explains why most AI initiatives fail, how leaders should rethink adoption, and what it takes to achieve measurable business outcomes.

Question 1: What are the most persistent misconceptions businesses still have about AI adoption, and why do so many initiatives fail to deliver results?

Brett Schklar: There are a lot of AI myths, but one of the ones that’s most important is not actually a myth, but an actual fact, which is that 95% of all new generative AI pilots fail.

That’s not a myth. There are other myths. AI is going to take us over. AI is replacing humans. There is some truth and some fiction to that. But the most important myth that needs to be overcome is the idea that deploying AI is an automatic formula for success, and that if you’re not doing it, you’re missing out.

Companies that are looking at technologies, evaluating them, and looking for a return on AI before they jump into things will help reduce that 95% of AI initiatives that are failing.

Question 2: What AI strategies actually drive sustainable business growth rather than short-term experimentation?

Brett Schklar: There are a couple of practical AI strategies for business growth that I help companies put together and organize. One of those is that this is a transformation that needs to happen top-down and bottom-up at the same time.

Employees need to feel empowered and autonomous to explore new technologies and capabilities that help them in their role. At the same time, leadership, the CEOs and business leaders, need to give employees the freedom to look at innovation and technologies that can really help.

This is not about getting 40% gains overnight or 50% gains overnight. This is about allowing every employee to get 1% better, then another 1% better, and those small, incremental gains continue to add up.

The second big thing that must be in place as a strategy for leveraging AI for business growth is building either a centre of excellence or a steering committee within the company. This should be made up of cross-organisational functions and people who are most passionate about what AI can do for the business.

Question 3: Where are companies misunderstanding AI’s role in workplace innovation, and where does it deliver the most measurable impact?

Brett Schklar: AI is doing a great deal to drive workplace innovation. It is the essence of workplace innovation, but it’s doing it in a way that’s different from what many people expect.

A lot of companies think AI is going to create huge gains in a very short period of time. Twenty per cent gains, thirty per cent gains, more efficiency, better targeting, more growth. The reality is that where AI really helps drive businesses forward is by empowering each employee to look at how AI can help them in their job to get 1% better, 2% better, or 3% better.

These small step gains across an entire organisation are far more effective than a large initiative forced from the top down, which can stall, slow down, and face significant resistance.

Question 4: What forms of AI-related anxiety are you seeing at the executive level, and how can leadership teams address them effectively?

Brett Schklar: I have witnessed a lot of AI anxiety among CEOs and leadership teams. That ranges from fear driven by what Hollywood has taught us to believe about AI, to fear of being left behind.

Ultimately, the best way to overcome fear or anxiety with any new transformation is not to try to get ahead of it, but to help the organization understand it. Building centers of excellence or steering committees allows people across the business to feel more empowered and more capable of leveraging AI in their role. That helps overcome AI anxiety. Otherwise, the fear continues to grow.

Question 5: How is AI reshaping leadership priorities and decision-making inside modern businesses?

Brett Schklar: AI has completely redefined leadership in business and how business gets done.

When AI is implemented correctly, it removes many of the mundane, repetitive tasks that people dislike doing. When AI or AI agents help eliminate those tasks, leaders are able to become better thinkers, planners, and strategists.

Also, when companies embrace AI and commit to learning how to remove repetitive work, they begin thinking differently, growing more effectively, and building plans that can actually be executed, rather than plans that remain hopes and dreams.

Question 6: What should leaders focus on today to future-proof their organisations as AI capabilities continue to evolve?

Brett Schklar: One of the secrets to future-proofing leadership in the age of AI is being truly agile, and understanding that what you put in place today may be outdated or no longer serve you three months from now.

The second focus should be measuring the return on AI. Leaders need to ask whether a technology, tool, or system is a fun technical project or a science-fair-style experiment, or whether it is truly an initiative that will help the business grow and produce meaningful returns.

This exclusive interview with Brett Schklar was conducted by Tabish Ali of the AI Speakers Agency.

Benzinga Disclaimer: This article is from an unpaid external contributor. It does not represent Benzinga’s reporting and has not been edited for content or accuracy.