AI in 2023: Generative models are dominating the scene

Companies that have integrated artificial intelligence are pioneers in harnessing the potential of generative AI. Those who derive significant value from conventional AI are already ahead in adopting generative AI instruments. The anticipated business disruption due to generative AI is profound. Organizations foresee substantial shifts in their workforce, expecting reductions in some areas and extensive retraining to meet evolving talent requirements. 

Although generative AI's emergence might encourage the uptake of other AI technologies, there hasn't been a notable rise in the adoption rate. The proportion of businesses utilizing any AI tools has remained consistent since 2022, with its use primarily limited to a few business areas.

A recent McKinsey Global Survey highlights the rapid rise of generative AI tools. Within a year of their introduction, a third of respondents reported that their companies use generative AI in some business functions. AI's prominence has shifted from just tech circles to top management. About a quarter of C-suite executives personally utilize generative AI tools, and over a quarter of AI-adopting firms indicate generative AI discussions at board levels. Furthermore, 40% plan to up their AI investments due to generative AI advancements. 

The use of generative AI is already widespread

The survey from mid-April 2023 indicates that even with generative AI's recent introduction to the public, its experimentation is already widespread. Respondents foresee these new tools revolutionizing their sectors. Generative AI's allure spans diverse demographics, with individuals from various regions, sectors, and ranks using it both professionally and personally. A notable 79% of participants have encountered generative AI in some capacity, and 22% integrate it regularly into their tasks. While usage consistency is observed across ranks, it's most prevalent among tech sector professionals and those in North America.

Companies are increasingly adopting generative AI. A third of respondents indicate their firms consistently use generative AI in some capacity, translating to 60% of firms that have embraced AI. Additionally, 40% of those with AI integration anticipate increasing their AI investments, driven by generative AI's potential. Interestingly, 28% mention that generative AI discussions have reached boardroom levels. The primary business areas deploying these advanced tools mirror where AI is predominantly used: marketing, sales, product development, and service operations, including customer support and administrative tasks. This trend implies that firms target generative AI where they see the most benefit. Past studies have indicated that these sectors, along with software development, could account for roughly 75% of the annual value derived from generative AI applications.

High hopes and expectations

As generative AI emerges, 75% of respondents anticipate it will bring significant or transformative shifts to their industry's competitive landscape within three years. Those in the tech and financial sectors are most optimistic about generative AI's disruptive potential. Past studies indicate that while all sectors might experience some disruption, the intensity will differ. Knowledge-intensive industries are set to face greater upheavals and possibly gain more value. For instance, tech firms could see value addition equivalent to nearly 9% of global industry revenue.

Similarly, knowledge-driven sectors like banking, pharmaceuticals, and education might see value boosts of up to 5%, 5%, and 4%, respectively. On the other hand, manufacturing-centric sectors like aerospace, automotive, and advanced electronics might witness milder disruptions. This is a departure from past tech trends that majorly impacted manufacturing, highlighting generative AI's prowess in language tasks over physical activities.

Going all in on artificial intelligence

The survey underscores that organizations attributing at least 20% of their 2022 EBIT to AI wholeheartedly embrace both generative and traditional AI capabilities. These trailblazers are leveraging generative AI more extensively than their counterparts, especially in areas like product development, risk management, and supply chain operations.

When considering the full spectrum of AI, including machine learning, robotic automation, and chatbots, these high performers are more inclined to harness AI for product enhancement, from refining development cycles to innovating AI-centric products. They also frequently deploy AI in risk assessment and HR functions, such as performance management and workforce optimization.

Interestingly, while many organizations prioritize cost-cutting, leading companies have a different vision. They're twice as likely to view generative AI as a tool for spawning new business avenues or revenue streams. They also emphasize the augmentation of existing offerings with fresh AI-driven features.

Historical data reveals that these frontrunners consistently outspend others in AI. They're over five times more likely to allocate a fifth of their digital budgets to AI endeavors. Their AI adoption is also more pervasive, spanning multiple business functions and integrating many AI tools. For instance, they're more prone to embed knowledge graphs and natural-language capabilities into their operations.

Even the best haven't perfected AI adoption practices

However, even these high performers aren't without challenges. Their hurdles often stem from their advanced AI maturity, such as refining models and tools. In contrast, other organizations grapple with foundational AI strategy issues, like aligning AI vision with tangible business outcomes.

The data also hints that even the best haven't perfected AI adoption practices, like machine-learning operations (MLOps). Yet, they're ahead of the curve. For instance, 35% of AI high performers prioritize reusing existing components over reinventing the wheel, starkly contrasting with 19% in other organizations.

Specialized MLOps practices are essential to harness generative AI's transformative potential safely. One area of focus is live-model operations, where real-time monitoring and alerts ensure generative AI systems remain controlled. High performers lead the way here, too, with a quarter having comprehensive monitoring compared to a mere 12% of their peers.

AI is expected to change the workforce in meaningful and radical ways

The survey unveils evolving roles that organizations are targeting to bolster their AI endeavors. Over the past year, AI-centric organizations predominantly onboarded data engineers, machine learning engineers, and AI data scientists—roles frequently highlighted in the prior survey. However, there's a noticeable dip in hiring AI-related software engineers, who were the top recruits last year (28% this year, a drop from 39% previously). Additionally, as generative AI gains traction, roles in prompt engineering are emerging, with 7% of AI-adopting respondents noting such hires in the past year.

The data suggests that while recruiting for AI-centric roles remains a hurdle, it's slightly eased, possibly influenced by the tech layoffs wave from late 2022 to mid-2023. Compared to the previous survey, fewer respondents found challenges in hiring roles like AI data scientists and data engineers. However, recruiting machine learning engineers and AI product owners remains persistently challenging.

Redefining roles

The consensus is that AI's integration will significantly redefine job roles in the next three years. The prevailing sentiment is a tilt towards reskilling employees rather than layoffs. Nearly 40% of AI-adopting respondents anticipate reskilling over 20% of their workforce, while a mere 8% foresee a workforce reduction of more than 20%.

Zooming in on generative AI's projected influence, most respondents anticipate a workforce reduction only in service operations. This aligns with recent insights suggesting that while generative AI might automate 60-70% of tasks (an uptick from the earlier 50%), it doesn't equate to automating entire roles.

Lastly, AI high performers are charting a distinct path. They're poised for extensive reskilling, with respondents from these entities being thrice as likely to project a reskilling of over 30% of their workforce in the ensuing three years due to AI's influence.

AI adoption and impact remain steady

Even as generative AI tools gain traction, the survey indicates they aren't the primary drivers of overall AI adoption in organizations. The percentage of organizations embracing AI remains consistent, with 55% of participants confirming their organization's AI adoption. Only a minority, less than one-third, report AI implementation across multiple business functions, hinting at a restricted AI application scope. The dominant areas for AI adoption remain product/service development and service operations, consistent with findings from the last four surveys. Interestingly, a mere 23% attribute at least 5% of their previous year's EBIT to AI usage, suggesting vast untapped potential.

Furthermore, organizations acknowledge the benefits in sectors where AI is deployed and are optimistic about future investments. A significant majority have observed AI-driven revenue growth in functions utilizing AI. In terms of future prospects, over two-thirds anticipate ramping up their AI investments in the coming three years.