For us consultants in the AI world, the only thing to fear is fear itself, and fear is a triangle. Every AI project triggers three types of uncertainty: Personal (social pressure, preconceived notions), Financial (ROI and job loss concerns), and Organizational (infrastructure gaps). Most try to solve all three at once. That's a mistake. Pick the two fears that move the needle. Let the third wait. Momentum beats perfection. Read on to find out why.

The most foundational framework that we Data & AI consultants can use is the simplest one you can think of: impact vs complexity.

In this article, I explain the differences between the two and how they come together to enable Data & AI strategies to become real, how we can use it in workshops to serve clients, and how you should be thinking about them.

Data & AI leaders no longer just build insights, they roll snowballs, starting small and building unstoppable momentum through four key principles: momentum over perfection, small and early over big and late, building for humans not processes, and understanding that value is a feeling not a metric. Read on to find out why!

Data projects fail because consultants fix individual issues in isolation instead of addressing the entire ecosystem: a cycle where sourcing, ingestion, storage, governance, visualization, and automation all depend on each other.

Superposition's assessment workshops use structured facilitation and gamification to reveal these cyclical connections, transforming vague client problems into properly scoped projects with clear roadmaps clients actually understand and sustain.

Most SMBs struggle with data not because of technical limitations, but because they lack the human processes (alignment, trust, and translation between technical and business teams) that make data actually useful. In this post, we talk about the key to creating just enough structure so your team can make confident decisions, starting with one specific business problem where better data makes a measurable difference in 90 days.