Will the AI Bubble Pop in 2026? – Navigating AI Investment Realities

To be or not to be – that is the question concerning an AI bubble popping in 2026.

I will cut to the chase on this one – it won’t. That’s it, so do you need to keep reading?

Well, yes, you need to know the reasons behind this belief, what could happen to change my mind, and more importantly, how to steer your company away from any potential impact.

But first, let’s look at the reasons behind this mass speculation of an impending burst which has been making headlines on a daily basis for months.

Unpacking the Fear: Investor Panic and AI Investment Surge

Probably the biggest fear driving this hype is panic from investors. Millions upon millions of dollars are being pumped into that AI balloon every day with every investor and venture capitalist hoping to land on the next big gold mine. Private AI investment has grown more than thirteenfold since 2014, reaching $252.3 billion in 2024, with a significant portion (over $33 billion) focused on generative AI. Any slight whisper that money may be lost quickly sends shock waves around the investor community and the business world, with start-ups and other corporate entities worried about their annual budget or where the next round of funding will come from. Just recently when big billionaire investor Peter Thiel announced he’s pulling out of AI stock Nvidia, it fueled yet more jitters about a deflating AI balloon.

The ROI Dilemma: GenAI’s Struggles and Corporate AI Experimentation

GenAI has definitely been the catalyst for the hype and boom for investments, but apart from concerns on profit margins and over inflated valuations, alarm bells have now begun to ring among enterprise compliance, security and legal officers advocating responsible, trustworthy AI and policies for model risk management.

On top of that came an MIT study reporting that 95% of GenAI investments are not returning any ROI with most being stuck in the pilot or experimentation phase, leaving many organizations questioning their AI investment altogether.

This brings me to the real problem behind the anxiety over a bubble burst – companies diving in feet first without properly evaluating their true needs and how best to address them.

FOMO and Its Fallout: How Hasty AI Deployments Cause Operational Chaos

We’ve already seen what can happen when businesses jump all in without having a strategy – chaos among staff and IT. In fact, 60% of IT decision makers who we surveyed in 2024 admitted that their driving factor for investing in AI was FOMO. Yes, fear of missing out on the next big thing and potentially allowing rivals to get one step ahead caused knee jerk reactions for many decision makers.

Fast forward a year to ABBYY’s most recent study – conducted by Opinium Research in July – showing that business leaders have increased spending on the latest technology, GenAI, yet most are struggling to work with it.  Nearly a third (31%) discovered training GenAI models is harder than expected, while 28% say the tools were difficult to integrate due to challenges with data and current processes. In addition, 26% did not have proper governance, and worryingly, a fifth (21%) say staff are misusing GenAI tools and the same number are suffering potentially harmful hallucinations.

But here’s the kicker. The majority of respondents admitted to needing other technologies to save the day. 1 in 4 (40%) of US businesses introduced AI agents, over a third (36%) turned to process intelligence, 31% augmented with Document AI, and 23% added retrieval augmented generation (RAG).

The Multi-Tool Approach: Combining GenAI with Complementary Technologies

Enhancing GenAI with these other technologies resulted in business leaders seeing better consistency of outputs (58%), better integration into existing workflows (50%), more accurate and reliable results (48%), greater cost efficiency and savings (44%) and increased user trust (42%).

The lesson is clear, indiscriminate spending on GenAI often fails to deliver value. Businesses are spending money on tools that promise more than they can provide. In some cases, they don’t even need it. It’s actions like this that fuel fears of an AI bubble as companies reflect on their failures, with potentially low ROI starting to ring alarm bells. When leaders stop following the herd by continuing to throw money at the latest shiny technology, the AI bubble will stop inflating.

Strategic Steps Forward

Before moving forward with leveraging GenAI tools or agentic AI, businesses need to first evaluate current processes and create a visibility map of the workflow using sophisticated data analytics tools that flag problems, pinpoint automation opportunities and monitor performance.

The OpenAI’s of the world will continue to disrupt, bringing new ways to solve real world problems – but they will never be a one-stop-shop. Other vendors and technologies will always be needed to get there. The Wall Street Journal recently noted that LLMs may get the hype, but small models are necessary to get the value companies need from their tools. It cites a study from Nvidia and the Georgia Institute of Technology which noted that AI agents are being used for narrow, repetitive tasks which small language models are much more suited to. People will start to recognize how they can keep costs down, realizing that there is no need to train a model on 30,000 documents and burn through compute for something a regular expression could do just as well. Also, the open-source community is advancing rapidly, giving customers more options to choose from and experiment with.

So, to sum up, there will still be ample investments in AI in 2026, but on more purpose-built tools that are focused on solving a real business problem, as the C-suite realigns priorities and takes stock of the impact needed vs promises delivered thus far. Vendors that define a path to success and use technology with common sense will prevail – and that AI boom will keep on expanding, driven by strategy, tangible revenue and demand, not hype.