Empowering people is essential to fully harness AI's benefits and mitigate its disruptive impact..
The profound impact of generative AI is becoming increasingly evident. This technology is set to revolutionize industries and reshape the job landscape. To navigate this immense change and fully leverage AI’s capabilities, leaders must focus on empowering and developing their people. Investing in the workforce is key to harnessing the benefits of AI while managing its disruptive effects.
1
Trillion-Dollar Narrative
Three Scenarios of Human-Driven Productivity
2
Dissecting Job Evolution
Unveiling the Scale of Change through Exposure and Friction Scores
3
Envisioning 2032
Anticipating Strategic Evolution with Increased Adoption Rates
4
Novel Trust Framework
Four Recommendation for Maximizing Productivity
5
Concluding Thoughts
The Power of Strategic Decisions in Ensuring Generative AI’s Benefits for All
6
Insights
A Deeper Dive into Our Model and Exposure and Friction Scores
Summary
With the rise of generative AI on the global stage, anticipation grows for its transformative impact on the economy, businesses, and society at large. Questions loom regarding the scale, timing, and ramifications of these changes—will they be constructive or disruptive, embraced or feared?
Emerging insights paint a picture of significant magnitude. Our research suggests that by 2032, generative AI could infuse an additional $1.043 trillion annually into the US GDP—an economic surge equivalent to the entire US construction industry.
Anticipated is a surge in the adoption of generative AI, with projections indicating that up to 13% of companies may embrace the technology within three to four years, and nearly half within a decade, in our most optimistic scenario.
This projection not only underscores the potential of generative AI to revolutionize tasks across diverse sectors but also signals a fundamental reimagining of work, productivity, and economic dynamics.
In quantifying the productivity impact of generative AI and its implications for the future of work, our collaboration with Oxford Economics yielded an economic model. This model delineates three scenarios reflecting varying levels of business adoption.
Critical to navigating this transformative landscape is the cultivation of trust—between AI developers and users, businesses and policymakers, and employers and employees. While trust across these realms is paramount, our emphasis lies in fostering trust within businesses and between employers and employees, where proactive measures can optimize the productivity potential of generative AI.
Now is the opportune moment for leaders to forge a new trust framework, ensuring that generative AI serves as a catalyst for positive economic growth while benefiting workers and society. Success in this endeavor holds the promise of unparalleled prosperity and efficiency. Conversely, failure may precipitate prolonged unrest and discord, as evidenced by emerging tensions among AI developers themselves.
Natural Language Processing (NLP)
General AI excels in NLP tasks, enabling machines to understand and generate human language with increasing accuracy. Applications range from chatbots for customer service to sentiment analysis in social media.
Businesses adopting generative AI
in 3-4 Years
in 10 Years
General AI enhances computer vision capabilities, enabling machines to interpret visual information from images or videos. This technology is pivotal in autonomous vehicles, facial recognition systems, and medical imaging diagnostics.
Decision Making
AI algorithms in General AI can simulate human decision-making processes based on vast datasets and complex patterns.
By embracing the following tenets, organizations can take the crucial first steps to bolster confidence, build trust and open the door to a new age of productivity and prosperity.
1: Take care of your people
Roll out strategic reskilling programs at a pace and scale never seen before.
2: Innovate or stagnate
Plan for how you’ll operate and create value in a decade’s time.
3: Build confidence with transparency
Show how AI outcomes will serve the broader goals of business and society.
4: Put AI gains to good use
The wealth generated from AI also needs to benefit the workforce and the world.
Robotics Integration
General AI integrates with robotics to perform tasks autonomously in various environments. Applications include manufacturing, logistics, and even household chores through advanced robotic systems.
Generative AI is a breathtaking feat of technology that could have a substantial impact on society and the economy. But the way it plays out will be grounded in deeply human factors. Will we resist or welcome it? Adapt or stay unchanged?
The extent of that impact will be determined by the rate of business adoption and how quickly people adapt to working in new ways. These factors have historically slowed other productivity innovations. For example, microprocessors arrived in the early 1970s, but it took two decades for personal computers to be widely adopted and for productivity gains to materialize.
This is why we worked with Oxford Economics to develop three adoption scenarios.
If business adoption of gen AI is low, the annual productivity boost in the US could grow to 1.7% by 2032. Even this bearish estimate represents a significant upswing, given that the long-term annual average US growth hovers around the 2% mark. And if adoption comes in at the high end, that figure could soar to 3.5% by 2032 (see Figure 1). From the perspective of total economic output, this means US GDP would see a boost between $477 billion and $1 trillion in 10 years’ time.
Three scenarios for gen AI impact on US GDP
Generative AI could inject anywhere from $477 billion to $1 trillion into the US economy by 2032, depending on the level of business adoption.
Ethical AI Developmentspan
As General AI advances, ethical considerations become increasingly important. Organizations focus on developing AI systems that prioritize fairness, transparency, and accountability to mitigate biases and ensure responsible AI deployment.
Generative AI is a breathtaking feat of technology that could have a substantial impact on society and the economy. But the way it plays out will be grounded in deeply human factors. Will we resist or welcome it? Adapt or stay unchanged?
The extent of that impact will be determined by the rate of business adoption and how quickly people adapt to working in new ways. These factors have historically slowed other productivity innovations. For example, microprocessors arrived in the early 1970s, but it took two decades for personal computers to be widely adopted and for productivity gains to materialize.
This is why we worked with Oxford Economics to develop three adoption scenarios.
The extent of that impact will be determined by the rate of business adoption and how quickly people adapt to working in new ways. These factors have historically slowed other productivity innovations. For example, microprocessors arrived in the early 1970s, but it took two decades for personal computers to be widely adopted and for productivity gains to materialize.
This is why we worked with Oxford Economics to develop three adoption scenarios.
If business adoption of gen AI is low, the annual productivity boost in the US could grow to 1.7% by 2032. Even this bearish estimate represents a significant upswing, given that the long-term annual average US growth hovers around the 2% mark. And if adoption comes in at the high end, that figure could soar to 3.5% by 2032 (see Figure 1). From the perspective of total economic output, this means US GDP would see a boost between $477 billion and $1 trillion in 10 years’ time.
Three scenarios for gen AI impact on US GDP
Generative AI could inject anywhere from $477 billion to $1 trillion into the US economy by 2032, depending on the level of business adoption
Advancements in General AI
General AI represents a significant leap in technology, with applications spanning from enhancing human-machine interaction through NLP and computer vision to revolutionizing industries via autonomous decision-making and robotics. Ethical considerations guide its development, ensuring AI systems are not only intelligent but also fair, transparent, and accountable in their operations, fostering trust and ethical deployment in society.