We’ve seen this over and over again in the business technology space over the last several decades: organizations invest thousands, hundreds of thousands, or even millions, of dollars, euros, rupees, or pounds on the latest technology and make it their own. Leave it to the workforce, expecting overnight miracles in productivity and growth. Then, nothing happens – or things go even.

It all boils down to one thing – poor leadership, or even lack of leadership, especially now when it comes to AI. Unfortunately, if anything, AI seems to be paralyzing business leaders — and even disabling their technology counterparts. They don’t understand the implications of new technology, or refuse to immerse themselves in it. But they must be able to overcome the pitfalls, and help their organizations realize the possibilities that AI offers.

That’s the word from David D. Cramer, dean of Northeastern University’s business school, who urges business and technology leaders to put aside any trepidation and take the plunge and learn the ways and means of AI. In his latest book, The AI-Savvy Leader: 9 Ways to Take Back Control and Make AI Work, De Kramer points to one of the many failed examples where the plug was pulled on AI projects: “Leaders They seemed paralyzed by the introduction of this new worker called AI. They couldn’t articulate how and why AI would be useful in achieving the company’s goals.

The rapid development of AI, he writes, “puts leaders in the awkward position of learning to adapt while simultaneously learning what they are adapting to.”

As a result, “leaders are less confident about what they think their role should be when adopting AI.” At the same time, their employees and colleagues are expecting more. “They expect their leaders to be proactive in the use of AI governance, so that their employees can work more efficiently”.

A lack of understanding about AI actually leads to a sense of inadequacy among business leaders, de Kramer says. “This sense of inadequacy prevents them from being actively involved in guiding their organization’s AI journey.”

He explains that executives in de Kramer’s advanced leadership classes at Northeastern “feel so stressed about AI that some wonder aloud if they need to educate themselves as professional coders to be effective AI leaders.” Need to change.”

The answer is no, business leaders don’t need to be AI experts, “but they need to understand that they only need to know about AI to recognize its benefits,” advocates de Cramer. . This includes identifying opportunities in teams’ workflows and projects and staying on top of developments in the AI ​​field.

They emphasize promoting in-house workshops and on-the-job training, to advance both executive and staff understanding of AI. Invite experienced industry peers, professors, and consultants to guide such learning.

Crucially, De Kramer says, to successfully lead AI efforts, it’s important that leaders make it their mission to develop AI to help people do better work — not Automate them from their jobs. Do business leaders see AI “as a way to automate tasks, thereby augmenting human capabilities so that we can take on newly designed jobs, but not as a way to completely replace us?” I’m not quite sure.” Unfortunately, he adds, many see AI as an augmentation strategy, versus an alternative, “too expensive and risky.”

“What would be the value of a business world where humans eventually have nothing to do but follow the same streamlined operations that AI follows? What if an organization undergoes industrial changes that require workers who Able to think creatively, actively participate in innovation, and communicate empathetically with customers?

This requires a high level of emotional intelligence as well as technology skills on the part of the leader. “Accept that soft skills are the new hard skills and practice them,” says De Kramer. “To become an AI-aware leader, invest in developing your emotional intelligence skills. You need to break out of the technology manager mold and begin to behave as change and human-driven strategies. will be what organizations involved in AI adoption need.

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