How Business Leaders Can Use GenAI

If you think that GenAI can only impact lower-value tasks or simplify mundane processes, then you are underestimating its potential. According to a new report on HBR, GenAI can even serve as a tool for business leaders or even the CEO to augment their strategic thinking and decision-making. 

It explored two business cases to highlight how GenAI was able to help businesses overcome blind spots and predict the future, as well as address trends and develop scenarios to take advantage of them.

Overcoming blind spots

The first case study focused on a commercial agricultural research organization. Concerned that perspectives identified by the executive team might be biased due to their professional training and industry experience, they turned to GenAI to produce a fresh perspective on key strategic issues that the organization is likely to face.

With the right prompting, GenAI identified four important areas that Keith’s team missed: technological advancements, regulatory changes, client demand and expectations, and funding and investment.

It is worth noting, however, that GenAI is non-deterministic, which means each response may differ. Moreover, GenAI could occasionally miss out on important factors. To mitigate this problem, business leaders can regenerate responses for alternative answers or prompt for additional ideas to avoid blatant omissions.

And while GenAI cannot answer questions about the future and do forecasting, it can provide fresh perspectives that can help executives think more broadly about demand.

Addressing trends

The second case study is by a firm in the funeral services industry. This time, the board of this business is able to provide a fresh perspective as they do not hold internal executive positions. 

However, with GenAI, the CEO was able to leverage GenAI to expand on the initial list with four more considerations, namely around “thought-provoking” suggestions such as changing demographics, mental health and grief support, price sensitivity, and regulatory changes.

When quizzed about the shortage of land for burials, GenAI was able to offer a range of suggestions. While some were laughable, it did come up with good suggestions for the organization to consider in the long term.

Retrieval augmented generation

Finally, retrieval augmented generation (RAG) is a technique where LLM outputs are blended with inputs from private data repositories. This approach provides up-to-date information from internal company documents to potentially offer new insights.

This capability is currently only available in enterprise-level GenAI tools and not currently available in ChatGPT and Claude.ai. However, a growing range of tools such as Google’s free NotebookLM and others offer the ability to easily “attach” up to scores of data sources that the LLM chat will incorporate into its answers.

Ultimately, while GenAI has limitations for strategic planning, its ability to analyze vast amounts of data makes it a useful tool to identify opportunities, mitigate risks, and offer suggestions to help business leadership develop robust strategies.

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