The Generative AI Surge: A Dotcom Bubble in the Making?

Every other week a brand new AI tool seems to be coming to the B2B market offering new and improved features on its predecessors. From a valuation of $136.55 billion in 2022, the global AI market is at an astonishing $298 billion valuation in 2024. In 2025, it is forecasted to reach $420 billion, with expectations soaring to a staggering $1.847 trillion by 2030. How big is this bubble going to get?

Last year at the HBMA - Houston Business Marketing Alliance Interactive Strategies Conference, I moderated a panel discussion of experts on AI in B2B marketing. Thank you to?Chris Ferris, PhD,?Divya Visentini,?Maryna Burushkina, and?Erin Moore?for participating in the panel and sharing their insights with me and my colleagues.

On the subject of AI tools and workflows for marketing teams, Divya remarked that it was her prediction for AI technologies to start merging with one another to create a more cohesive and possibly more holistic workflow pattern. She continued, the tools used today will have to come together because there's no practical way teams can function with 50 different tools for 50 different things. It will all come down to how quickly people adapt to certain platforms to manage all functions in marketing, cohesively.

The rapid rise and inflation of new technology seems reminiscent of the dotcom bubble.

The Dotcom Bubble Making Technology History

In the late 1990s, the dotcom bubble was fueled by overinvestment and overvaluation in internet-based companies, leading to a market perception disconnected from reality. Investors were dazzled by the prospect of quick profits, despite many of these companies generating little revenue. The bubble burst due to rising interest rates, disappointing earnings, and flawed business models, causing most companies to lose their value overnight.

If the generative AI industry does not heed the lessons from the dotcom bubble, it may be destined to repeat the same catastrophic downturn. Whether or not the technology is here to stay is not in question, we know the product is sustainable across industries and functions in every aspect. However, there must be roots in viable business models that prioritize real value creation for AI companies, and their clients. Otherwise we will see a repeat of the same failures as companies struggle with high operating costs and the pace of technological advancement.

The Rise of Generative AI in B2B Marketing

B2B marketers are proving particularly adept at utilizing artificial intelligence to conduct business better. Through personalized sales and marketing techniques, enhanced data analysis, creativity and innovation, improved campaign effectiveness, and more streamlined content production, B2B marketing companies are using the tools at their disposal extremely effectively to increase their ability to generate revenue.

For instance, Canva , the design software company, has moved past its beginnings as a service to make images and videos. It has fully integrated AI into its offerings, which has significantly impacted its revenue and the services it provides to its customers. The company's early bet on AI has led to the rollout of a suite of new AI-centric products, contributing to a 21% jump in its annualized revenue, from $1.4 billion to $2.7 billion.

However, Canva is facing challenges of rising operational costs and has to face questions about their pricing models for AI products. The variable consumption costs and development costs associated with their new service offerings are not yet stabilized. They are continuing to prioritize awareness and market share capture with heavy content marketing campaigns and advertising.

Overlap and Redundancy in AI Tools

The generative AI market is becoming increasingly crowded, with many new tools targeting similar markets. Large companies are incorporating AI into their products to remain competitive. This trend can lead to market inefficiencies and confusion among organizations seeking AI solutions.

As market saturation grows, industry consolidation through mergers and acquisitions is likely. However, some believe that this initial saturation is a necessary stage for future innovation. Dominant tools like ChatGPT will face competition from new entrants, which could concentrate market share and potentially hinder competition and innovation.

Large, established companies can attract top talent and reduce costs, scaling their outreach and leveraging modern branding and storytelling. This could further challenge smaller players in the AI space.

A Challenge of High Operating Costs and Low Profits

Managing costs while in the black or red is a hurdle that budding AI companies will have to get past and find ways to become profitable. The high development and time costs associated with keeping their products competitive leave little margin for overhead. The computing power alone for these business models to remain substantial and continue fueling company growth are mountainous. The investment required is high, and is expensive to maintain. AI models need near constant updating, re-training, and fine-tuning to meet consumer expectations.

OpenAI , the AI research company, reportedly doubled its losses to $540 million in 2022, primarily due to the high costs associated with developing and training AI models, and hiring key employees from Google. Revenue has picked up, reaching an annual pace of hundreds of millions of dollars just weeks after the launch of a paid version of ChatGPT. The company is reportedly generating around $80 million a month and is on track to generate more than $1 billion in annual revenue.

To avoid a bubble burst similar to the dotcom one, AI companies must develop new business models that allow them to manage costs effectively and find innovative ways to monetize their technology. They need to focus on creating value and achieving productivity gains that justify their investments, ensuring sustainable growth and profitability.

The Future of the Generative AI Market

The anticipated growth in the market is to be driven by increased demand for AI products that make their clients money, and the wide breadth of industries who can enjoy it.

The key to unlocking the full potential of generative AI lies in the delicate balance between innovation and sustainability. B2B marketers must leverage AI to create genuine value for their clients, transcending the allure of novelty to deliver tangible results.?B2B marketers must remain vigilant, learning from the lessons of the dotcom burst to navigate the generative AI wave with prudence and purpose.?