Over the past year we’ve witnessed dramatic strides in AI development and huge shifts in public perceptions of the technology.

Chatbots like OpenAI’s ChatGPT and LLMs like GPT-4 have demonstrated remarkable abilities to communicate fluently and perform at or near the highest level on a broad range of cognitive assessments.

Companies that are integral to the AI ecosystem (like Nvidia) have seen their market caps soar. Talk of an AI arms race among tech giants like Google and Microsoft is ubiquitous.

Despite all the excitement surrounding AI, there has been no shortage of consternation, from concerns about job displacement, the spread of disinformation, and AI-powered cyberattacks all the way to fears of existential risk.

Although it’s essential to test and deploy AI responsibly, it’s unlikely that we will see significant regulatory changes within the next year (which will widen the gap between leaders and followers in the field). Large, data-rich AI leaders will likely see massive benefits, while competitors that fall behind on the technology or companies that provide products and services under threat from AI are at risk of losing substantial value.

There will be winners and losers in the AI race, but AI pessimists are discounting the creativity and productivity that the technology will unleash. Yes, job losses are inevitable, but so are job gains. The most successful companies won’t fight the tide of change – they will figure out how to take part in one of the greatest technological revolutions we have ever witnessed.

Innovation will counteract dislocation.

There’s no doubt that AI will replace many existing roles, such as data entry clerks, content creators, paralegals, customer service agents, and millions of other workers may discover that their careers are about to take an unexpected turn.

Accenture expects 40% of all working hours to be affected by LLMs alone, as “language tasks account for 62% of the total time  employees work.”

The World Economic Forum’s 2023 Future of Jobs Report projects that the proportion of tasks done by machines will jump from 34% to 43 % by 2027.

That said, it’s always wise to bet on human creativity and resilience. As some roles become redundant, there will be increased demand for AI auditors and ethicists, prompt engineers, information security analysts, and so on. There will also be surging demand for educational resources focused on AI.

PwC reports that a remarkable 74% of workers say they’re “ready to learn a new skill or completely retrain to keep themselves employable” – an encouraging sign that employees recognise the importance of adapting to new technological and economic realities. Perhaps this is why 73% of American workers believe technology will improve their job prospects.

Companies should take advantage of these sentiments by focusing on talent mobility and professional development, which will simultaneously prepare their workforce for the AI era and improve retention in a stubbornly tight labour market.

Beyond internal training, we’re seeing the emergence of third-party educational services focused on AI, data science, cybersecurity and many other forward-looking subjects. This trend will likely pick up momentum in the coming years.

Amid all the dire headlines about AI-fueled job losses, it’s important to remember how adaptable human beings can be.

Managing AI risk will be a core priority.

On top of the economic shocks that will be caused by AI, the technology poses many other dangers that companies and consumers will need to account for in the coming years.

AI-powered cyberattacks, problems with bias and transparency, copyright infringement, and the large-scale production of inaccurate information are all risks that are becoming increasingly urgent. The ways we manage these risks will have sweeping implications for the deployment and adoption of AI in the coming years.

Consider the potential role of AI in cyberattacks, for instance. According to Verizon’s 2023 Data Breach Investigations Report, almost three-quarters of data breaches involve a human element, which is why cybercriminals often rely on social engineering attacks such as phishing.

LLMs are capable of producing limitless quantities of coherent and compelling text in an instant, which could potentially give cybercriminals a powerful tool for scaling up phishing attacks (these attacks are dependent upon convincing victims they should click on malicious content with realistic-sounding text).

Check Point Research has already identified “attempts by Russian cybercriminals to bypass OpenAI’s restrictions.”

Companies will increase their cybersecurity investments to keep pace with these developments, and we will likely see major AI-enabled cyberattacks in the near future. It will be necessary to update approaches to cybersecurity training to account for the threat posed by AI.

Phishing attempts, for instance, will be harder to spot because cybercriminals will use LLMs to produce convincing (and less error-filled) text. Companies in the best position to succeed during the AI revolution are the ones that are considering the risks now and updating their compliance protocols, HR policies, and cybersecurity platforms to account for the dangers of AI while leveraging its benefits.

AI will fundamentally transform the business environment.

ChatGPT soared to 100 million monthly active users in just two months, which makes it the fastest-growing consumer application of all time. While large tech companies with access to enormous amounts of data and leading minds in the field will have significant first-mover advantages, many startups will develop innovative implementations for AI in the near future. The economic impact of AI will go far beyond the development of the technology itself.

For example, the fusion of AI and robotics, as well as new collaborations between mechanical, electrical, and software engineers, will shrink innovation cycle times, error rates, and costs dramatically.

Over the next year, AI-led disruption will pick up momentum swiftly: workforces will shift, there will be drastic fluctuations in market share and valuations, and slow AI adopters will lose traction quickly.

There will also be many false starts: while some companies will generate staggering returns, others will fall for misdirected hype and run into dead ends. The most successful startups will find a way to capitalise on network effects around data acquisition and partnerships with first movers.

It’s impossible to know exactly what the business landscape will look like as AI rapidly improves and proliferates. But one thing is certain: forward-thinking companies are right to focus on AI now – they just have to be cognisant of the risks along with the potential rewards.