Stay Grounded

#LeadershipInTheAgeOfAI

In this era of humans working with machines, being an effective leader with artificial intelligence (AI) takes a range of skills and activities. In this series, I provide an incisive roadmap for leadership in the age of AI.

The world is enraptured with progress in AI, and sometimes it seems like public dialogue diverges from what is factual and likely. AI is in the news every day, on the agenda for every organization and on the mind of anyone paying attention to technology innovation.

With the emergence of generative AI (GenAI) models that can produce content that appears to be created by a human, the enthusiasm is now reaching a fevered pitch. Hyperbole seems to be ruling the day, with fears of workforces being entirely replaced by machines to even more outlandish predictions better suited to a Hollywood movie script than a serious discussion of a revolutionary technology.

It can be difficult to parse what is real from what is the product of over-active or overly cynical imaginations. Leaders have a role to play in this moment. We need to hold onto a grounded perspective of just what is happening with AI and what it means for our collective future.

Yet, even for professionals with a keener understanding of AI model types, worries may be eclipsing rational expectations. In my organization, Deloitte’s, State of Generative AI in the Enterprise, Q1 report, more than half of survey respondents said they expect GenAI to increase economic inequality, and 49% said they believe GenAI will erode trust in institutions. This tracks with business leader sentiment around AI more generally. A 2022 Deloitte survey found 50% of respondents cited AI risk management as a top inhibitor to scaling AI projects. How do we square the intense excitement and expectation with pessimism and concern around AI risk?

The reality is the world is in a transitional phase with this technology. It is daunting and complex, but eventually, the dust will settle and give way to an AI-fueled world where value is clear and risks are mitigated. Leaders in this AI era can help their organizations chart a path through this period of rapid change by maintaining a calm, measured and realistic view of AI. This is not the first time we have encountered a transformational technology.

The Three Streams Of AI Progress

Whenever a new technology reaches the marketplace, development and adoption tend to occur along three parallel streams. While they take place simultaneously, they do not often progress at the same speed.

1. Core Technology Development

Through an iterative path of innovation, the technology itself is developed and improved. It is commonly fueled by R&D investment, be it commercial or sometimes more academic in nature. With AI, I've noticed this stream is receiving most of the attention and investment.

2. Implications From Technology Adoption

A learning curve emerges as new iterations of technology are deployed in the real world. Problems and opportunities are discovered, leading to decisions around risk management and technology governance. Treating these issues requires adapting workforces, systems, organizations and even society to responsibly use the new technology. AI has received some treatment in this stream, although progress and investment are not occurring at a pace commensurate with technology development.

3. Policy And Rulemaking

As the technology is adopted and deployed at scale, larger societal implications become clearer. While industry guidelines and leading practices are established, public sector organizations take up the task of codifying laws and regulations to govern how the technology can be safely and legally used. Bureaucracies rarely move as quickly as innovators, and to be sure, laws and rules follow the lessons learned in technology adoption. Still, this stream of progress is often slow, as it has been in AI thus far.

These parallel streams occur for any transformative technology. Consider automobiles. The first Model T was sold in 1908 ; the first three-point seat belt was invented in 1959 ; and it was not until 1968 that U.S. federal law began to require vehicles be fitted with seat belts. The pace of innovation vastly exceeded the streams of managing risk in technology adoption and establishing rules to enforce responsible use, but the transitional period eventually gave way to a world where automobiles are commonplace, the risks are well understood, and effective laws are in place.

Looking to AI, a similar trajectory is playing out. Investment and hype are centered on the stream of technology development, with somewhat less attention given to understanding and mitigating risks. Policy and rule makers worldwide are, predictably, moving a bit slower still. Change is hard, and it takes time and leadership. In the longer arc of history, our progress through this transitional time is proceeding as I would anticipate.

Unlike in the transitional period for automobiles, we today have social media, where AI narratives can gain attention even if they may not reflect reality. This ongoing digital dialogue can lead us to presume things about our future with AI, but the truth is not at the extremes of anticipation and fear. Enterprise leaders need to be the cooler heads that prevail, keeping AI discussions and investments grounded in reality while still maintaining an optimistic, forward-looking mindset.

Taking A Measured View Of AI

While the future with AI is today uncertain, the world will likely navigate through this time of change and emerge on the other side where AI is as common and controlled as the family car. Precisely what that future looks like, however, depends on where we focus our time and energy, and the greatest and most valuable future with AI will not occur without attention and investment.

For enterprise leaders concerned with AI adoption risk, the task is not to turn away from AI but instead to make commensurate investment and effort in all three streams of progress. That is how we can accelerate the transitional period in a responsible way and get to the serious business of accessing AI’s greatest value for all.

Originally published at https://www.forbes.com/sites/forbesbusinesscouncil/people/beenaammanath1/?sh=33cfc0b2bd3e