Six phases for creating effective AI innovation units

Published

12 months ago

January 20, 2025

As artificial intelligence continues to transform industries, businesses face an urgent choice: adapt or risk irrelevance.

In an era of rapid technological advancements, AI innovation units have emerged as vital tools for businesses to maintain competitiveness and adapt to transformative trends.

Establishing an AI innovation unit requires careful planning across six key phases; Hardik Jagda, Founder and CEO of Proximity Works explored these key areas during his exclusive interview on Ticker.

First, assess your readiness by auditing data infrastructure and addressing gaps to lay a solid foundation.

Next, set clear, measurable goals tied to business outcomes, ensuring alignment across teams.

Partnering with external AI experts can fast-track progress while mitigating risks, especially when internal expertise is limited.

Prioritise high-impact projects that deliver tangible value, then follow a structured approach: build, test and scale successful initiatives.

Finally, embed adaptability by fostering a culture of innovation and continuous learning, enabling your organisation to stay agile and resilient in an ever-evolving technological landscape.

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