AI adoption does not start with technology, it starts with a clear view of the problems worth solving and the data you already have.
Ann Miller
May 22, 2025
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The strongest AI initiatives begin with a specific, measurable business challenge, reducing support response time, forecasting demand, automating document handling. Define where intelligence would change outcomes before evaluating any technology.
AI learns from your data. A discovery session that maps your objectives, challenges, and data readiness reveals where AI can deliver measurable value, and where groundwork is needed first.
Most enterprise-grade AI solutions are completed within 8 to 20 weeks after requirements are finalized. Start with one high-impact workflow, prove value, and expand from a working foundation.
Enterprise AI needs strong governance, transparent methodologies, and reliable engineering. Whether integrating into your existing ecosystem or building from scratch, trust and safety must be engineered in from the start.
A single workflow with a number attached. Not "explore AI".
Find where the relevant data lives and how usable it really is.
Prove value on one workflow before expanding.
Industrialize the win; do not start five pilots at once.
Most companies are earlier on the curve than they think, and that is fine.
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Get your readiness scoreGetting started with AI is a strategy exercise before it is an engineering one. Define the outcome, validate the data, pilot fast, and build on what works.
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