Generative AI and chatbots will not be something the world has never seen before 2022. It’s not even about Siri or Alexa, but the nice old ELIZA, certainly one of the primary examples of Natural Language Processing, who could be a 57-year-old lady now. Nonetheless, only half a century after, when Chat GPT and other notable large language models proved the technology as commercially viable across an unlimited spectrum of industries, businesses understood that they needed Generative AI solutions, as soon as possible.

Few of them, nevertheless, realize what they need Generative AI for, and even fewer understand the complexity of the duty and the resources required. Here’s where we are available in – accelerators and consulting corporations.

Made-to-measure or ready-to-wear?

An excellent suit, tailored in response to the person measurements from preferable fabric, color and with a selected occasion in mind, is a worthy investment. People, wearing such suits, don’t worry about their look. They know they give the impression of being perfectly and feel accordingly. A customized AI technological solution, which is made to achieve particular business goals, has enhanced security and perfectly integrates into corporate systems, is an actual James Bond suit.

That is a great comparison, which supplies a general idea. But let’s dive a bit deeper into the explanations most enterprise corporations prefer to not implement ready-made AI solutions, even from market leaders:

To begin with, effective Generative AI integration is inconceivable without highly individual work for every company, which requires a separate team, informed concerning the company’s strategic development plans, goals, and resource availability. A Generative AI solution, which appeared workable for one company, will probably appear useless for one more one.

Secondly, a smaller startup will fully immerse into the corporate’s specifics and offer a made-to-measure solution from a team of AI experts, who’re able to working with open-source models, securely training them on corporate data, and placing them on the client’s servers. This enables to create an on-premise solution and comply with the necessities of secure data deployment and storage, which is a priority for enterprise corporations.

What do corporations need Generative AI for?

As Gen AI is comparatively a newcomer to the company market, the most important method to gain experience and make progress is thru trial and error, which implies launching pilots. Until we’ve got enough benchmarks across various sectors, that is by far the best method to find an answer that completely suits the corporate’s unique needs.

Nevertheless, there are particular trends in corporate requests for Generative AI solutions:

1. Smart text and voice bots based on LLMs to supply high-quality assistance to customer support and support queries of various complexity levels.

2. Worker AI assistant (i.e. sales manager’s helper, which analyzes a real-time conversation with the potential customer and concurrently generates ideas and customer offers for a specialist)

3. Copilots for developers

4. HR solutions for recruitment and onboarding automation

5. Marketing tools: images and avatar generation, writing articles, and product reviews.

‘No Gen AI is required’ – that is the conclusion that some customers don’t expect to return to, but readily agree with after analyzing the corporate’s current state and business goals. AI for the sake of AI is a waste of resources, which the technology is known as to eliminate.

Generative AI Market Opportunities

In keeping with PitchBook’s estimation, the Generative AI market will reach $42,6 billion by the top of 2023 and is anticipated to grow at a CAGR of 32% to achieve $98,1 billion by 2026. These predictions don’t bear in mind the potential of generative AI to expand the entire addressable market of AI software.

That is compared with 22.6% CAGR for the AI industry as an entire, which implies that GenAI will proceed to overperform relative to the larger industry.

If estimates aren’t convincing enough, here’s an illustrative fact from our experience as an accelerator. After the turbulent 2022, which is related to the economic recession and a rapid decline of enterprise investments, Intema acceleration programs switched focus from fundraising to launching pilots with corporations.

In 2023, Intema held two acceleration programs with absolutely different dominant technologies: Metaverse and Generative AI. Throughout this system, we connect startups with corporate customers to debate potential technological solutions, arrange demos and, if successful, make agreements on the potential pilots. The Metaverse acceleration program resulted in 4 pilots with corporate clients, which is great taking into consideration the technology’s specifics and complexity.

The Generative AI program, even several weeks before its termination, had 7 pilots in discussion with a spread of corporations. So is that this just the effect of a hype that used to surround Blockchain and Metaverse before? Or is it because Gen AI is an actual game-changer?

It All Comes Down To the Query: Is GenAI Well worth the Hype?

First off, it just isn’t unusual for a brand new promising tech or an idea to get overhyped within the short term, perhaps to the drawback of its longer-term prospects. If we proceed draw parallels between GenAI and Blockchain, at its preliminary maturity stage, blockchain has been described by many as a technological revolution, which is able to reshape the world, very like GenAI is touted today. Nonetheless, years later, in 2018, Gartner announced that blockchain has entered the Trough of Disillusionment, which also corresponds with greater than a 30% drop in consumer interest from peak levels and a forty five% decrease in VC investment from 2018 to 2019.

Versus blockchain, at its early maturity stage, GenAI already has many use cases across an unlimited spectrum of industries which can be commercially viable. Their number is anticipated to grow as more industries adopt GenAI solutions. In its recent publication, Gartner placed generative AI technology at the height of the so-called “hype curve,” which indicates that there could be a correction in expectations and a few type of disillusionment within the near future.

Conclusion

Does it mean that after such a large demand for Generative AI solutions, the technology is doomed to get off the radar? This scenario is unlikely, for GenAI has already proved its fundamental tenability and adaptability in various spheres of human activity, from science to art to provide chain.

Nonetheless, a slowdown in technology development is inevitable, with the most important cause here being the urgent need to regulate and regulate the usage of GenAI. Up to now, this instrument has been utilized relatively freely, with none legal constraints. Legal regulation will set a brand new trajectory within the technology’s evolution path, and it’s hard to predict where it is going to go, for GenAI with its current abilities is wholly unprecedented in human history.

The opposite factor, expected to limit Generative AI in the longer term, paradoxically is the growing size of enormous language models. In the end the capabilities of AI chips won’t meet up with the event of the technology, and the aspiration to construct Artificial General Intelligence and the growing volumes of knowledge require highly complex engineering and rather more computing power.

These limitations, nevertheless, open an unlimited field for research, experiments, and non-standard approaches to LLMs lossless compression, computing power growth, data storage, etc.