Conversations about artificial intelligence (AI) and jobs often revolve around the reallocation of tasks and skills as society prepares for the 2.3 million new jobs AI will create by 2020. However, AI’s impact transcends manual tasks. The strategic, high-level skills of business leadership are also set for disruption.

For many leaders, the changes have already begun. Today’s more innovative leaders are preparing now to work alongside AI in order to redefine leadership. With the emergence of new roles — some that are still being defined — leaders are leaning on AI to ask questions that weren’t previously economical to answer, as well as questions they didn’t even know how to ask.

What common leadership practices are likely to change? Here’s a look at some common management practices in the path of AI’s disruption:

The Org Chart

Companies of all sizes and industries rely on org charts to map roles and responsibilities, with the goal of defining roles and promoting task delegation across various lines of business. Tasks are then dispersed to the proper department, with the chart serving as the catalyst to find voids in existing roles or map roles effectively across departments. Org charts have also historically been used as tools to guide career development, with professional progress often measured in terms of “moving up the org chart.”

Digitalization is diminishing the value of org charts as tools for understanding how work is done in a company. Relationships and roles in modern companies are not as rigid as the straight lines of an org chart would have you believe. People work cross-functionally, with little thought to formal reporting relationships. Similarly, using org charts to guide career development no longer makes sense for most professions. Lateral moves are becoming just as important as upward moves to career development, if not more so.

With the right data, AI can be used to gain a better understanding of how work is done in a company where the org chart no longer means what it once did. AI can map out which employees have the greatest impact and where there may be talent gaps. AI is also proving useful in helping employees identify what job moves — lateral, upward, or otherwise — are likely to have the greatest benefit for their long-term career growth.


People will always be the crux of any company’s success, as there is no replacement for creativity and interpersonal collaboration. However, AI can help equip a company’s people to perform at their best. Specifically, AI will redefine the staffing and hiring process by providing the answers to questions such as, “What training does this employee need to get to the next level?” AI can also help leaders identify when it’s better to look for external talent and when a promotion or internal candidate would be best.

Additionally, AI can help leaders enter new markets more seamlessly, as AI can inform leaders whether a geographical area’s talent and business conditions offer a viable opportunity for expansion. These same data points help leaders understand how to best staff a location and compare salaries by region.

Leaders must treat artificial intelligence the way they treat new employees entering the company: trust them a little bit at a time, watch the outputs, and coach/adjust as they go. Leaders should understand that AI is not a magic elixir to fix all problems, and blind trust can create algorithmic bias or lead to systems without the oversight necessary to ensure the algorithms perform optimally.

However, with trust and time, AI will have a positive impact. Those leaders who are open to exploring new technologies and willing to test new processes will be most successful.

Today, the C-suite is morphing into the “solution suite.” Gone are the days when leaders could solely rely on gut instincts to make key business decisions. Leaders who learn to work alongside AI, using it as a tool to support but not replace traditional leadership decision-making, will thrive.

Steven T. Hunt is senior vice president of human capital management research at SAP SuccessFactors.

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