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However, no business is the same and navigating the complexities of AI adoption can be daunting.
Experimenting is great, but only with purpose.
What opportunities can AI address?"
Your purpose could be enhancingcustomer experience, streamlining internal processes, or optimizing decision-making, for example.
Clearly defined goals provide a roadmap for your AI journey.
It also helps you avoid the tempting trap of adopting AI for the sake of it.
Focus on specific needs and align your AI initiatives with your overall business strategy.
Chief Architect and AI Officer, Solace.
This is where robust data governance practices and integration solutions come into play.
Data silos are the enemy of AI.
They stop AI from being able to learn, evolve and provide meaningful and valuable insights for yourbusiness.
Breaking down silos requires organizations to invest in data governance practices and data integration solutions as a priority.
Quality data is the fuel that powers quality AI.
Engineer your bespoke AI platform
Developing AI applications can be slow, hindering their potential value.
Platform engineering can act as the much-needed accelerator.
This emerging trend has the intention of modernizing enterprise software delivery, particularly for digital transformation.
Additionally, it optimizes the developer experience and accelerates product teams delivery of customer value.
The overarching focus is on streamlining infrastructure, automating tasks, and providing pre-built components for developers.
Last year, IDC found that only 12% of organizations connect customer data across departments.
AI adoption must not chase the latest trends but focus on making strategic investments that deliver tangible business value.
We’ve listed the best IT management tool.
The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc.
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