How AI Influences Strategic Decisions

How Does AI and Automation Influence Strategic Decisions at the C-Suite Level?

The impact of AI and automation on corporations globally is very evident. The AI market is poised to surpass $56 billion by 2026.  However, the rise of Generative AI tools like Bard and ChatGPT is forcing C-suite executives to think outside the box on how to gain a competitive edge through strategic decision-making. Here are five ways artificial intelligence and automation influence decision-making at the C-Suite level.

5 Ways Artificial Intelligence Influences Decision-Making

1. Eliminating prejudice

One of AI’s biggest strengths is minimizing the possibility of unconscious human bias that often leads to poor decision-making. C-Suite executives can use AI tech like machine learning and cognitive computing to analyze large data sets and make data-driven strategic planning decisions.

In other words, company heads can leverage AI to achieve the best results in customer service,  HR, and many other areas of operation.  Over the years, many leaders have realized how discrimination, whether intentional or unintentional, can cost a company in terms of money and equity. Thanks to AI, no one has to worry about bias or the accusation of bias.

2. Capacity planning 

C-Suite executives are very familiar with the art of strategic thinking. They often must pose questions such as: 

  • How will changes in legislation affect their businesses?
  • How can our supply chains withstand disruptions, and for how long?
  • Where do we introduce new products and break into new markets?

Today, inflation and global conflict have dramatically increased supply chain pressures and driven capacity planning jitters. AI technology, including data visualization and natural language processing, can help executives take mitigative measures when faced with disruptions that threaten to undermine their strategies established for the near and long term.

3. Risk management

CFOs and CIOs are massively adopting AI in risk prediction and mitigation.  Financial institutions are using AI-powered tools to manage credit risk and automate financial services tailored to match the needs of their users. User and event behavior analytics (UEBA) tools can detect and respond to anomalies in transactions and financial reports. In IT, automation and ML algorithms also help to bolster a business’s ability to identify information related to cybersecurity risk management. 

4. Predicting future needs

With the help of AI tools, executives can analyze large data sets and make accurate predictions.   It is now possible to work with historical data going back decades, analyze market trends, and predict demand and market fluctuations. This level of foresight has proven beneficial in inventory management, pricing, marketing, and other business functions. It helps to avoid resource wastage, minimize losses, and maximize productivity and profitability. One major bank uses AI technology to extract and analyze big data on supplier contracts.  They matched that with invoice numbers and identified millions of dollars in new opportunities for services and products not provided.  

5. Customer satisfaction

We’ve reached a point where competitive advantage is measured exclusively by the ability of a business to analyze volumes of client data and use AI to optimize the customer journey. 

For instance, C-suite executives can implement AI intelligence experience engines to personalize customer journeys and introduce various self-service options.  Vanguard has piloted an AI agent that responds quickly to all the frequently asked questions customers post.  This has allowed customers to engage with the technology directly and not via a human, thus saving the company time and resources.


AI and automation have a tremendous transformative effect on strategy formulation at the C-suite level. As AI systems demonstrate their value, business leaders slowly become believers in AI. AI can identify patterns, automate operational decisions, and predict limited outcomes. C-suite execs are, therefore, making more data-driven decisions in a timely and precise manner.

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