Jamie L. Robinson, Founder and CEO, RCSG / Corvus Link.
Starting a new business can be a leap into the unknown. The main question I think you should ask when starting a business or pivoting to a new one is whether to trust your instincts or rely on data.
In 2024 alone, the world is expected to generate 149 zettabytes of data, with Statista projecting that figure ballooning to 394 zettabytes by 2028. The challenge? Transforming this deluge into actionable insights.
These days, it may seem easier to just trust your gut and let it lead your business to growth and prosperity. However, relying solely on intuition can leave you blind to critical patterns and opportunities that new tools are helping expose.
EY reports that AI is reshaping industries at unprecedented speeds, driven by geopolitical shifts, economic disruptions and technological advancements. For decision makers, this raises a critical dilemma: Is instinct enough when faced with change on this scale? Or should the data—however overwhelming—be your guide? Enter AI, the bridge between intuition and information.
Facing A World Of Data And Change
Imagine a human resources (HR) director swept up in the recent layoffs from what many are calling the “white-collar recession.” He leaves a comfortable job with a Fortune 500 company with years of experience and many ideas he had planned to implement at the company.
Instead of returning to another HR role, he decides to take a chance to build a product based on his ideas that he believes will transform how HR is employed in the age of AI and remote work. His experience tells him demand is rising due to the influence of AI and remote work in the workplace, but the competition is fierce.
He consults reports, market forecasts and financial models but quickly falls victim to “too long; didn’t read” (TL;DR). After reviewing a mind-numbing amount of structured and unstructured data—customer preferences, organizational designs and evolving regulations—the aspiring HR product leader finds clarity elusive.
I find “data prep” and “data cleansing” are common pain points for decision making. I’ve witnessed teams spend an inordinate amount of time talking over each other because they didn’t feel their contributions were represented in the data, which led to stymied decision making. Also, teams may unknowingly feed unreliable data into a decision making process and appear bewildered when the decision doesn’t produce the expected outcome.
This is where instinct often takes over. The entrepreneur feels the market will reward bold moves, but his gut also signals caution. This push-and-pull creates tension, leaving him to wonder: Is there a better way to handle the uncertainty?
As he deliberates, it becomes clear an urgency exists to influence consumer behavior before demand shifts or peaks. To this point, the earlier cited EY report predicts that AI-driven disruptions will accelerate in the next five years, impacting sectors from healthcare to transportation.
For the entrepreneur, these changes compound the complexity of their decisions. With so much at stake, trusting only instinct feels risky. At the same time, analysis paralysis is a real risk when faced with too much data.
AI As The Decision Maker’s Ally
In an age of too much information, AI can be a counterbalance, enabling our entrepreneur to move quickly on launching their product while making better-informed decisions. It offers something unparalleled: The ability to process and analyze large datasets in real time and distill insights that account for human factors like intuition.
In the case of our entrepreneur, AI could help forecast staffing needs based on regional trends, simulate operating models and even evaluate competitors’ strategies. This integration bridges the gap between intuition and information, creating a decision making model that is both human and data-driven.
In practice, our entrepreneur might evaluate the relationship between price indices and employment for their industry to get a sense of how sensitive staffing might be based on factors like inflation. Or he might consider recent events to assess whether they are cyclical, short-lived or the beginnings of something transformational.
In this new era of information, the GOFER model—goals, options, facts, effects and review—remains actionable with AI. For example, the entrepreneur sets a goal (launching an AI-enabled HR product), evaluates options (onshore versus offshore technical talent), consults facts (real-time market analytics), assesses effects (AI-modeled HR impacts) and conducts reviews (continual data updates).
Each stage of the model is manageable when the entrepreneur can accept or challenge their instincts and the data with support from AI. Our entrepreneur might test latency with integrations by running a pilot of his product with data from free sources (e.g., government, nonprofits, etc.) to prove the concept. Each step in the GOFER model is enhanced by AI, allowing our entrepreneur to make decisions and execute them quickly.
Building Confidence In AI-Driven Decisions
Armed with AI, the entrepreneur no longer has to choose between gut instinct and data. Instead, he makes decisions rooted in both.
As long as our entrepreneur remembers that:
• A bad input can lead to a bad output.
• AI is not all-knowing and requires context.
To ask clarifying questions that can validate AI outputs, our entrepreneur is going to need to have a powerful relationship with AI. He should be able to effectively work with this tool to predict trends, adapt to changes and, most importantly, act with confidence at a time of great uncertainty. Trusting his gut remains vital, but with AI, it becomes informed intuition rather than a shot in the dark.
For entrepreneurs facing an era of vast data and unending change, the choice isn’t binary between your gut and the data. Whether you’re launching a new business or steering an established one, I encourage you to embrace AI as a partner. Let it handle the complexities of data and weave in intuition so you can focus on strategy, creativity and vision. The future is uncertain, but with AI, decision making can be a little less so.
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