Infinite Analytics


Five Steps To Develop An Effective AI Strategy

by Team IA, July 7, 2021

We get a lot of queries about how to make AI an intrinsic part of the work culture. We feel that to achieve an overhaul that your business needs, it involves developing a solid strategy to get a competitive edge with smarter business decisions in your pocket. All you need is dedicated trained resources, and a bit of your time and investment for it to show results. Sharing the secret sauce on how YOU can develop an ace AI strategy!

Set clear goals

The vision and its execution should be one. It is often seen in Artificial Intelligence transformation projects that these two get separated which leads to complicated and scattered programs which take long to bear fruit. To avoid this one must use AI solutions based on clear goals or business objectives.Business strategy should be in tandem with quantifiable goals to facilitate the deployment of Artificial Intelligence. Besides, reviewing the strategy itself would do wonders. Evaluate if the current business strategy still works for you and check if there are any changes in the priorities.

Have the right personnel

To implement your AI strategy you need to have a multi-faceted team for R&D, engineering, analytics, design etc to enable you to achieve the business goals in a planned and systematic order. Furthermore, establishing a work culture which encourages experimentation will help you find the apt AI assets.

Data strategy

As the goals are set clearly by now, you need to lay out your AI priorities which could be to make your business processes intelligent, automating repetitive tasks so as to free up manpower for other work, and also automating your manufacturing processing (if that is the nature of your business). But before all this you need to ask the right questions i.e. if you have the right data, and if not how will you obtain it; if you have enough data; if you will be using third-party data or would you be setting up new data collection methods etc.

Baby Steps

Transforming your current products or services into AI-based solutions  can’t be achieved at the drop of a hat. You need to implement the short-term AI priorities first, to add value and then aim for bigger projects involving AI. Look for processes which have the potential to be transformed quickly and in an inexpensive manner. Go on a fact-finding mission to lay the groundwork for your bigger AI dreams.

Data governance and ethics

Data governance ensures data obtained from a variety of sources is reliable. This is especially important if your nature of work comes under the scanner of a lot of regulations. Equally important is data privacy and security. Any legal implications arising by way of your data source or consent or privacy need to be looked at too.

Lastly, know that AI is an evolving process. Once you’ve executed the plan and proven its competitiveness, you must keep improving it every now and then.

If you are developing your AI strategy, and need help or guidance, do write to us at


by Team IA

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