With over $35 billion invested in AI startups so far this year, combined with a projected market of $1.8 trillion and an economic impact of $15.7 trillion, AI investment and M&A are expected to boom.
AI Artificial intelligence is front and center at Mobile World Congress 2024, where AI-enabled mobile phones, virtual reality glasses and human-like robots that interact with humans will be on show in Barcelona, Spain, 2024. (Photo: Marc Asensio/NurPhoto via Getty)
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Throughout history, technological innovations have often gone through painful phases accompanied by waves of frustrating hype and exaggerated claims. A modern example is Amazon's “Just Walk Out” system, touted as a wonder of artificial intelligence-driven shopping convenience, which relied on human reviewers scrutinizing video feeds from stores. Similarly, the Metaverse was touted as the next big thing, leading Facebook to prematurely change its name to Meta. AI can also be discredited as hype, based on the gap between marketing promises and functional reality.
However, AI holds great potential in various fields and sectors, including the healthcare industry. Consider the COVID-19 pandemic, when pharmaceutical companies were racing against time to develop a vaccine. Regardless of their stance on vaccines, Pfizer scientists were able to create an mRNA vaccine with the help of machine learning (ML), shortening the time curve required to analyze patients' clinical data.
Since then, companies have been focusing on implementing task-specific AI solutions, with AI technology playing a major role in enabling drug discovery, medical diagnostics, and supply chain management. With emerging InsurTech companies such as Vertigo incorporating AI capabilities into their platforms, we can expect to see the impact of AI across various sectors, including banking, financial services, and the insurance industry.
While AI ushered in a new era of innovation and practical applications, consumers also got a taste of AI with the introduction of OpenAI's ChatGPT in 2023. The year marked a turning point where AI capabilities finally caught up with consumer expectations. It also helped create a notable distinction between AI focused on analysis, problem-solving, and decision-making, and AI-based solutions that can create new content as a result of conversations, now known as generative AI (GenAI).
Last year saw an unprecedented surge in the development of machine learning models, with dozens of free-to-use GenAI models and platforms entering the market. Too many? Probably, but this is all part of the usual hyped-up hype cycle that either reaches a peak of inflated expectations or a painful valley of disillusionment.
According to a report by AI Index, the tech industry has come up with 51 AI models, academia with 15 models, and academic-industrial collaboration with 21 models. In 2024, the latest systems, such as GPT-4, Gemini, and Claude 3, are freely available to the public and can generate text in dozens of languages, process speech, and even participate in game and meme explanations. But what goes beyond the early days of text and speech toys?
Q2 2024 – A record-breaking gold rush
GenAI has made impressive advancements since its debut when it made its advanced models accessible, many of which will be paid for in the next wave. Companies are racing to use these advanced models to build AI-based products and services, leading to a surge in funding for GenAI, with billions of dollars being invested.
History often repeats itself, as fools jump in to be early adopters and become winners. But first-comers aren't always winners. Despite an overall decline in private investment in AI in 2022, funding for GenAI is expected to grow eight-fold, reaching $25.2 billion in 2023 and more than double in 2024, according to the AI Index report. The main players who secured funding were OpenAI, Anthropic, Inflection, and collaborative AI community provider Hugging Face (nice emoji name), which just acquired yet another company, XetHub.
Despite the looming trough of disillusionment, predictions continue that the AI market could reach $1.8 trillion by 2030, contributing $15.7 trillion to the global economy. Meanwhile, AI funding hit a record high of $23.2 billion in Q2 2024, according to CrunchBase. Expect a surge in investments and M&A as companies move to sell or acquire, extending their platforms beyond the capabilities and speed of first-wave deals. Recent deals include:
CoreWeave – $1.1B Series C, $19B valuation G42 – $1.5B investment, Microsoft Scale – $1B Series F, $13.8B valuation Wayve – $1.05B Series C, Softbank/Microsoft/Nvidia xAI – $6B Series B, $24B valuation
The first wave of technology is painfully frustrating
For example, the e-commerce sector is using AI to improve customer engagement metrics, while other sectors are trying to productize their own services. But not everything is perfect. For example, chatbots introduced to improve customer experience can sometimes backfire. In the case of delivery company DPD, an AI-powered online chatbot used rude language, sweared and criticized the company when interacting with customers. There are also examples of failed products. For example, the wearable personal assistant Humane AI Pin, despite being an interesting concept, struggled with battery life and AI reliability.
Pushing the boundaries is laudable, but it also needs to be strategic. There are lessons to be learned from the painful and frustrating days of building and using Web 1.0 services, when the technology was in its infancy and you had to “dial up” to the Internet, and from the dot-com bubble at the turn of the century. Fueled by hype and media attention, the stock prices of many Internet companies soared beyond their actual value at the time.
But despite the subsequent collapse, when the market eventually recovered, the Internet continued to evolve, with winners being companies, often second or third place, that bet on a wave of adoption of the most in-demand services that best optimized their underlying technology. This wave led to a market situation that some of Web1's founders regret: oligopoly. Many of us who helped create Web 1.0 and Web 2.0 would like to see a more democratized wave, away from the oligopoly and dominance of the Magnificent Seven often proposed in the belated promise of Web3.
Controlling or Opening AI Possibilities?
Some believe AI can start the transition to Web3, but the control and authority often resides in the leader's model, like Google's proprietary search algorithm. Hugging Face continues to shine a light on open source AI and supporting small communities. In a statement pledging $10 million in free shared GPUs to help developers build AI, CEO Clem Delangue said, “AI shouldn't be in the hands of a few. With this commitment to open source developers, in a spirit of collaboration and transparency, we look forward to seeing what everyone builds next.”
Collaboration helps. As AI's underlying technology matures, its impact on productivity, growth, and employment will become increasingly clear, leading to further adoption and more useful applications. McKinsey's 2024 Global AI Survey found that 65% of respondents will report their organization is using GenAI regularly in 2023, with overall AI adoption jumping to 72% in 2024.
Whether democratized Web3 and open source business models take hold, the next wave of AI applications will be incredibly powerful, empowering leaders to transform companies, industries, and society. As we move from the first wave of chatbots and co-pilots to autonomous AI agents, these next generation of LLM-powered bots (agents) will be able to reason and perform tasks independently across the enterprise. CxOs are testing these early agents with AI-enabled vendors focused on horizontal swim lanes that impact key areas of enterprise problems and opportunities, including sales, customer support, R&D, productivity, compliance, software development, engineering, and cybersecurity.
The Power of Enterprise Partnerships
GenAI adoption has the potential to be truly global, with companies across industries and business sectors exploring its use cases, advancing it, and testing its limits. Companies are racing to realize value from this adoption, but I strongly believe the smartest way is through strategic partnerships. It's not enough to innovate within your own industry.
Given GenAI's disruptive potential to transform workflows and drive competitive advantage, companies must look outside their organizations and sectors to gain the domain expertise they need to scale and develop fully integrated solutions. What CXOs need now is a GenAI strategy that makes business sense, is easy to integrate, and is secure. Admittedly, this is a big ask, and one that shouldn't be done alone.
In previous articles and broadcasts, we have discussed the smart money being put into next-gen AI organizations such as Kore.ai, which are driving Gen AI technology and large-scale language model (LLM) capabilities. These organizations are offering conversational AI solutions that have the potential to transform the way customers, agents, and employees interact with businesses, improving their experience and driving operational efficiencies.
In 2023, Mphasis, an information technology (IT) solutions provider specializing in applied technology and business process services, entered into a strategic partnership with Kore. The partnership will enable Mphasis to transform customer experience management and employee engagement to improve services for enterprise clients. Building an effective GenAI strategy requires understanding the benefits of the right partnership. Another example is the partnership with DeepInsights, which has developed an AI tool that can process documents, extract key information, and customize it to fit the specific needs of enterprises.
I met Nitin Rakesh, CEO of Mphasis, who, like many of us, uses ChatGPT in his free time to experiment with a variety of activities, like playing games, discussing pop culture, and even summarizing the literary classic “Romeo and Juliet” in two succinct words: “Love kills.” Awesome, right? But from his position as a CEO, he of course also uses the tool as a digital analyst, providing analysis, insights, actionable tips, and exploring business scenarios. And he's learned a few things along the way.
Meanwhile, you and many of your C-suite executives continue to experiment like this, but to what end? How do we move beyond the pain and frustration of the AI “toy wave” to impact business, industry, and even society?
Should executives move fast or slow?
Rakesh offers a word of warning to businesses moving forward with AI adoption, emphasizing that when leveraging AI tools, clear and focused instructions are essential for optimal performance: “Businesses need to train their employees to use these tools effectively, leveraging the imagination, simplicity and efficiency of GenAI while minimizing the damage. Ultimately, the purpose of integrating AI into any work process is to make people's lives easier, better and faster, without taking away jobs.”
Ah, the third rail problem. One that many business and government officials are hesitant to predict, much less discuss: the fight for jobs. Just like the waves of technology that have automated industry and enabled society since the early 1900s, AI will shape the future of work and life.
While the potential benefits of adopting AI are undeniable, it is not a silver bullet and companies should be cautious. Efforts must be made to ensure the technology they adopt is ethical and sustainable. Much of the responsibility for separating the hype from reality falls on senior management, who must provide clear guidance in the form of a clearly defined GenAI governance and strategy to not only the board but also those within the organization who will be using the tools.
Technology inflection points are a golden opportunity for organizations to seize the opportunity as surviving vendors settle on their best applications and business models while companies work hard to improve operational efficiencies and, more importantly, expand competitive offerings, global reach and competitive advantage. Companies that learned the right lessons in the early painful and frustrating days will be in the best position to lead the way.
