The recent explosion of AI-focused digital advancement has thrust businesses large and small into an accelerated future, serving as a catalyst for hastened digital transformation and deeper technological exploration. From the incomprehensible speed at which AI is evolving to the creation of revolutionary, AI-first products, companies of all sizes are diverting their focus to capitalize on these paradigm shifts and set their businesses apart over the long term.

Experts at this year’s Bridge Forum Summit, including Marc Andreessen, Co-Founder & General Partner at Andreessen Horowitz, Mustafa Suleyman, Co-Founder of DeepMind and Inflection AI, and Alexandr Wang, Founder and CEO of Scale AI, addressed the revolutionary impact that AI will have across industries and how companies can harness today’s technological tailwinds.

1) Why is AI considered the most revolutionary technology in decades?

For decades, engineers have been working on AI technology in pursuit of the belief that entire industries will reorient themselves around it and businesses will distinguish themselves by how well they use it. But, until recently, the struggle for humans and machines to interact and understand one another in natural language has stalled development efforts and hindered adoption by potentially billions of users.

This is now changing, thanks to one of the most important AI breakthroughs in the past decade: the arrival of large-language models (LLMs) powered by transformer architectures. This technology uses deep learning techniques and large data sets to understand, summarize, generate, and predict new content.

This new wave of AI has a vast array of applications – from redefining human-computer interaction to unlocking creativity and utilising data to drive efficiency through predictive analyses. LLMs are just the tip of the iceberg, however, as the world of AI is yet still largely unexplored by developers and commercial enterprises. With many different types of intelligence, such as reactive machines, limited memory machines, artificial narrow intelligence, artificial general intelligence, and many more, we can expect these “divergent paths to be explored simultaneously,” according to Mustafa Suleyman, Co-Founder of DeepMind and Inflection AI.

“Some of the most interesting AI breakthroughs in the last six months have started to use third party tools to call on existing knowledge bases or specialist AI models that have been designed for a specific context, rather than the general AI model where you have one AI that can do everything really well, like what you see with ChatGPT.”

2) How can companies build and use AI that actually works for their business?

AI’s ability to perform cognitive functions typically associated with human intelligence, such as perception, reasoning, environmental interaction, and creative expression, has material implications for the business world, potentially translating into enormous gains in operational efficiency and profitability. Ultimately, the value of AI for companies will come down to how successfully they deploy and integrate the technology into their business models.

To put AI to work, Alexandr Wang, Founder and CEO of Scale AI, said: “We always encourage organizers to start by identifying a single use case to demonstrate the power of this technology. From there, build and keep building it to scale.” Wang notes that while AI on its own has a great deal of potential, its likely to be most powerful when guided by humans, who can help it achieve more efficient and reliable work: “Empowering your employees, especially in areas where you know you there are large gaps in performance and giving them a co-pilot can be very powerful.”

Developing propriety generative AI models can be resource intensive and effective deployment of AI within large enterprises requires internal expertise as well as a thoughtfully-constructed API strategy. According to Suleyman, as knowledge proliferates, companies should consider building their own AI models for greater success.

“With AI, we have hyper evolution dynamics where the software is rapidly evolving because the demand is so great. And that’s great for businesses, individual users, and consumers because everybody is going to get access. This also means that companies really do have to attempt to build these models internally. And that means you have to invest in people and training and while that is expensive, I think it’s crucial, because otherwise you don’t really understand where the limits are.”

3) How is AI transforming the workplace?

AI is transforming the way we work, learn, and live. Within the corporate world, these technologies will evolve the nature of work itself as machines are able to carry out more of the tasks performed by humans today.

As a result, we can expect workforce changes, with many professional functions declining and growing in demand. According to Brian Franz, Global CIO of State Street, “we are at an inflection point of how we restructure what people do.” Some believe we should view these operational changes as a range, from as little as 10% of current work tasks being affected, to as much as 100%. A recent report by Goldman Sachs projected that Generative AI could replace as many as 300 million jobs.

“This is the most dramatic reorientation of talent I’ve probably ever seen in Silicon Valley and marks a rapid shift in the industry to use this technology.”

More importantly, however, companies will need highly skilled talent to effectively implement AI. But the problem is that there simply aren’t enough skilled professionals available, because, as Suleyman points out, “AI specialists are extremely rare and very expensive.”

This workplace transition, dislocation, and finite pool of talent requires that workers acquire new skills and adapt to the machines alongside of them.

“Unquestionably, many of the tasks that people do every day in ‘white collar land’ are unlikely to look the same in the next five to 10 years,” said Suleyman. What’s more important he believes is, “whether people are able to adapt, learn new skills, take advantage of the tools quickly enough and how that transition is managed by governments and big organisation.”