While much has been said about the role of artificial intelligence (AI) in enhancing tactical execution, it's high time we shed light on how AI can be harnessed as a strategic tool by senior executives to revolutionise leadership decision- making.

AI can empower leaders to set, inform, and adapt their strategies with unprecedented agility, all while leveraging effective, accurate, forward-looking projections derived from real-time organisational data.

AI: A catalyst for acceleration

In an era where data is the lifeblood of businesses, AI emerges as a powerful ally for leaders aiming to make impactful choices with heightened precision and efficiency. It moves past the conventional realm of automating routine tasks; instead, AI takes the centre stage in shaping strategy and driving growth.

Senior executives are often tasked with selecting the right Objectives and Key Results (OKRs) to steer a company towards its strategic objectives, but that is associated with a lot of time and effort. AI has the potential to transform this decision-making landscape by providing sophisticated analytical capabilities, pattern recognition, and immense data processing power.

Through the integration of AI, business leaders can easily identify the synergy between OKRs, spot the commonalities and align them with other parts of the organisation. This process could easily save time for managers as AI can predefine a draft set of OKRs for the upcoming quarter, based on past data and future predictability, therefore reducing the speed and operating in a pure “tool accelerator” fashion.

However, the largest waste saver of implementing AI is in making and preparing clear and optimal OKRs based on data analysis, and then reporting on the outcomes through a set of filters. An AI-generated report could cut down business’ costs, human mistakes and enable executives to adjust it according to their upcoming planned activities.

Uncovering hidden insights with AI

One of the most compelling aspects of AI's role in leadership decision-making is its ability to synthesise vast datasets using advanced algorithms and machine learning. This capability enables organisations to make informed, data-driven decisions, breaking free from the shackles of assumption and intuition.

The continuous tracking of OKRs is essential to business success, but that requires regular coaching, so employees can develop and refine the skills they need to achieve the set goals. This frequent feedback between resources can refine the ambitiousness and measure their alignment with organisational expectations. And this is where AI could come in handy.

AI has the capability to predict outcomes using recommendations based on historical data and ensure that OKR management is aligned with an AI-assisted analysis. The AI predictability relies on “sanitised data points" which are collected from various data sources to ensure these are meaningful, accurate and effective. The configurations need to be dynamic to allow for adjustments and changes, therefore, we need to overlay the AI prediction engine with a closed-loop control system to allow for adjustments and feedback.

This is how you build a robust, flexible, and scalable AI solution to address the ambiguity of data and arrive at a predictable outcome.

AI predictability can provide assistance on multiple levels, including:

  • Resource optimisation: Are the resources operating at their optimal level? This can be explored in two fundamental ways - AI analysis into the adequateness of the objectives and their alignment to the historical trend of the resources to which these OKRs are assigned to.
  • Objective alignment: If multiple OKRs are developed and assigned frequently that do not seem to have any relevance to the organisation’s strategic objectives, then AI predictability could advise the user on possible adjustments and improvements.
  • Future OKRs: What should we consider for the next set of OKRs? Before the OKR managers set aside time to think about it, the AI prediction engine will show one or more options with varying risks and success factors.

Enhanced business observability and collaboration

Senior executives and C-level staff have a pivotal role in charting the course for their organisations. One of the most remarkable aspects of AI is its ability to unveil patterns and trends that might elude human perception. These invaluable insights provide leaders with an augmented decision-making process, enabling them to see beyond the surface and delve into the nuances that shape their organisations. AI becomes an integral partner in the decision-making journey, offering perspectives that expand beyond the limits of human cognition.

The implementation of AI could boost teams’ collaboration and enhance the business observability. This could be accomplished in two ways:

  • Sentiment analysis: Usually, collaboration tools leave a footprint that is too often ignored. With AI, this footprint can be used to conduct an analysis to gauge the sentiment that has been applied throughout the OKR lifecycle. This can enhance user training, encourage teamwork and indicate early warnings concerning resources.
  • Pattern recognition: If there are user patterns that can be tracked regarding OKR management, they can be advised so that enhancements can be made upfront before an event occurs. Like a weather forecast, the OKR management should be aware of the team's structure and behaviour, to thereby encourage and/or correct patterns. For example, the OKR updates occur without attachments and/or supporting data. This can eventually fester and become problematic, or the OKR manager can choose to ignore these patterns. Over time, a team's signature pattern can be identified and therefore, when using AI predictability and resource optimisation, certain teams may be better suited to execute specific OKRs.

In the realm of leadership decision-making, AI is poised to be a game-changer. It offers senior executives the ability to make informed choices, enhance operational efficiency, and drive sustainable success. By leveraging AI's analytical capabilities, pattern recognition, and data processing power, organisations can transition from traditional, gut-feel decision-
making to a data-driven, agile approach.

Nick Kuc is CTO at Cronus