The Question to Ask Before Any AI Project: What Work Are We Trying to Get Rid Of?

The allure of Artificial Intelligence is undeniable, promising transformative solutions and unprecedented efficiencies. Organizations are eager to embark on AI projects, often driven by excitement and the ambition to innovate. However, this enthusiasm frequently overshadows a more fundamental inquiry: what problem are we truly trying to solve, and more specifically, what existing work are we aiming to eliminate or improve?

Before any code is written or significant investment is made, a strategic shift is required from can we use AI? to should we use AI, and for what precise purpose? As experts note, the key question isnt if AI is possible, but if it is the right choice for the specific challenge at hand Helge Tennø on LinkedIn. This article will explore the critical questions executives and data leaders must pose to ensure AI initiatives are grounded in practical value and avoid the pitfalls of technology-first approaches.

Beyond the Hype: Defining the Core Problem

Many AI projects falter not due to technical complexity, but from a lack of clear goals and strategy from the outset Helge Tennø on LinkedIn. The statement We want to use AI is an aspiration, not a plan. A truly effective AI strategy begins with a specific, measurable, and grounded in the business’s reality problem statement. If the problem cannot be clearly described and measured, the team is likely not ready to build.

This introspection naturally leads to asking: what specific tasks, processes, or inefficiencies are we looking to remove or significantly reduce? Identifying the work were trying to get rid of helps in pinpointing areas ripe for AI intervention—tasks that are repetitive, time-consuming, prone to human error, or bottlenecks in operations. By focusing on tangible pain points, organizations can ensure AI investments yield measurable improvements, aligning with the foundation before innovation principle.

Do We Really Need AI? The Human-AI Equation

A crucial, yet often missed, question is whether AI is genuinely necessary for the identified problem Helge Tennø on LinkedIn. AI becomes a worthwhile investment when humans can effectively query it and evaluate the accuracy of its outputs MIT Sloan. Tasks that consume a significant amount of human time are often strong candidates for AI-driven substitution MIT Sloan.

However, AI is not merely a replacement tool. Its best understood as a precision shock to the signals that guide human judgment, enhancing choices and productivity by clarifying information Helge Tennø on LinkedIn. This requires a double-literacy in human thinking and AI systems, and a doubling down on distinct human skills like critical thinking, creativity beyond data, and emotional intelligence to build trust in hybrid human-AI teams Helge Tennø on LinkedIn. The objective shifts from replacing humans to augmenting human capabilities and streamlining workflows.

Prioritizing People: Ethical and Inclusive AI Design

Alarmingly, many AI projects fail not due to technical hurdles, but because they overlook the very people they are intended to help Medium. This prioritization of technology over human impact leads to exclusive AI rather than inclusive solutions. To avoid these preventable problems, organizations must ask practical, actionable questions early in the process that ensure AI projects are inclusive, ethical, and truly serve the needs of their users Medium.

When asking what work are we trying to get rid of?, its vital to consider the human element:

• How will eliminating this work impact employees, customers, and stakeholders?
• Are we designing a system that genuinely improves the human experience, or merely automates for automations sake?
• What safeguards are in place to ensure fairness, transparency, and accountability?

Answering these questions ensures that the AI foundation is robust not just technologically, but also ethically and empathetically.

The journey to successful AI implementation begins long before the first line of code. It starts with strategic clarity, a deep understanding of the problems to be solved, and a commitment to leveraging AI to truly enhance human productivity and organizational value. By asking the critical question—what work are we trying to get rid of?—leaders can steer their AI initiatives toward impactful, sustainable success, ensuring a solid foundation before pursuing innovation.

To accelerate your AI strategy with expert guidance, explore resources in the AIDM Portal for frameworks, GPT tools, and executive AI training.

Key Takeaways

• Shift from can we use AI? to what problem are we solving? and what work are we getting rid of?
• Define specific, measurable business problems before initiating any AI project to ensure clear goals and strategic alignment.
• Prioritize inclusive AI design, ensuring solutions genuinely benefit people and consider ethical implications, not just technical feasibility.

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