Will big tech burst the AI bubble?

As artificial intelligence continues to reshape industries, a new battle is brewing between startups and tech giants. Companies like Perplexity are raising billions to challenge the dominance of Google, Microsoft, Apple and Meta. Still, the question remains: Will the AI wave create lasting winners, or is it a bubble waiting to burst?

AI search wars: Perplexity vs. Google, Microsoft, etc.

AI search company Perplexity has raised three funding rounds this year and launched a fourth, set to value the company at over $8 billion. The startup seeks to challenge Google’s supremacy in search by combining the best of traditional search functionality with providing answers to questions similar to ChatGPT. The company currently has annual revenues of slightly over $10 million (which means its valuation is 800 times its earnings). It recently launched an enterprise version for corporate customers that will search internal files. 

Last year, we signed an agreement with an AI startup that provided that same enterprise functionality. We didn’t renew because it’s now built into our Google Workspace platform, Gemini. We went from paying $150 per month to $10 per month for the same functionality. See what Google did there? 

Guess who else is playing this same game? Have you heard of Copilot, Microsoft’s new “AI Companion.” The partnership with OpenAI has all the bells and whistles of ChatGPT 4.0 (see below).

There is a free version and a Pro version (priced similar to Google Gemini at $30 a month) that will integrate into your Microsoft 365 suite. With a voice interactive interface (four voice options), you can delete your Amazon Alexa, Calm, Apple News and many other apps if you’d like. See what Microsoft is doing? 

Apple has quietly acquired more AI companies over the last three years than any other company in the world. Last year alone, they bought 32 AI/machine learning companies, almost twice as many as Microsoft. The new iPhone 16 with Apple intelligence is just the beginning. 

Let’s not forget Facebook, which is rolling out new tools via Meta’s Ads Manager. These updates, launching now and continuing into next year, will provide ad creatives with advanced background, image and text generation capabilities.

All of this is happening as marketers look to consolidate and/or reduce costs related to their martech stack. Up to 61% of respondents said the number one factor for a replacement solution was cost savings, according to the latest MarTech Replacement Survey. 

Dig deeper: AI readiness checklist: 7 key steps to a successful integration

Learning from past tech waves: Lessons for the AI era

Every technology wave brings winners and losers. It also creates an evolution, a better way to accomplish something. The dot-com bust gave us Amazon, eBay, Coupon.com and new ways to buy traditional products more efficiently.

The AI bubble will follow suit. It has already provided new ways to create code, images and content. But, outside of OpenAI and Anthropic, it’s uncertain who else in the AI generative space will be a winner. 

One thing is sure. We are only at the beginning of the wave of AI solutions. AI startups are currently getting one-third of all investment dollars, with B2B startups getting $10 for every $1 invested in B2C applications, according to CB Insights. As a result, we know we will see more AI applications aimed at B2B marketers. 

The marketer’s dilemma: Experiment or wait for integration?

For Perplexity, will it emerge as an AI winner, or will Google put it out of business by building its unique functionality into search? Marketers are facing a similar question, which may come down to opportunity cost. Is it worth the expense and time of learning a new tool, or do we play the waiting game to see if our current platforms integrate the functionality? 

Perhaps focusing solely on integration and costs is too narrow a perspective. Carrie Mahon, CMO at Unanet, offers a broader view: “Embracing new AI tools early not only provides marketers with a strategic advantage in creativity and efficiency but also fosters a mindset shift that speeds up AI integration and unlocks greater benefits. Delaying could mean missing out on these initial advantages and innovation opportunities in a rapidly evolving tech landscape.”

Could the real value and strategy lie in experimenting with new AI technologies, even if costly, and then transitioning to more efficient platforms as they emerge? Capture the opportunity to learn and innovate, then focus on efficiency.

As an old IBM client once said about new technologies, “Let a thousand flowers bloom, then cut them all down except for the tallest few.” He would then add, “Make sure that you tend to your garden!”

Perhaps the AI wave isn’t a bubble waiting to burst but a garden to nurture.

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