Solita services Data strategy

What is a data and AI strategy and why do you need one

What is a data and AI strategy and why do you need one

Bridging the gap between business strategy and practical data and AI development

Get in touch

The purpose of a data and AI strategy is to build a bridge from the organisation’s strategic choices into the discovery of opportunities for creating value with data and AI, and the development of practical capabilities required. The data and AI strategy should cover the entire data value chain from obtaining and managing essential data assets to generating actionable insights from analytics and business intelligence, and eventually delivering tangible value in the form of business use cases.

We have helped a multitude of organisations harness data and AI to create value for their business and their customers. Based on our experience, we believe that many organisations would benefit from a clearly defined data and AI strategy. Read what data and AI strategy is, why it matters, and how to get started.

Why having a data and AI strategy is so important right now

Several factors have converged to create a pressing need for a dedicated data and AI strategy that augments the overall strategy of the organization:

  • Rapid technological development such as Generative AI has opened up a host of new opportunities for creating value from data and AI, while at the same time rendering much of existing infrastructure obsolete and unfit for competition.

  • Consequently, the utilization of data and AI has become a crucial competitive factor, transforming it from the sole responsibility of IT into a central concern for every business function.

  • Often, the various parts of an organization seem to be on different data and AI maturity levels, leaving many people unsure of what data and AI mean for their role, and what is expected of them in the data-driven future.

Data strategy

Data and AI strategy is a vital management tool

A well-formulated data and AI strategy will equip the management with the right tools to tackle the aforementioned challenges by:

  • Ensuring that the organization focuses its scarce data and AI resources on those initiatives that yield the greatest strategic impact

  • Telling a compelling and inspiring story that helps everyone within the organization understand why data is important, what the organization is trying to achieve with it, and what is their own role in it.

  • Building confidence among stakeholders that the organization knows how to create value with data and AI and is determined to make it happen.

Data strategist

Data and AI strategy elements

Based on our learnings from the numerous clients we have worked with, we have composed a data and AI strategy framework that presents a structured, tried-and-tested approach to developing a successful data and AI strategy. It defines the main elements of a data and AI strategy, describes how they are connected, and provides practical guidance for conducting the strategy development process. Here is a quick overview of the main elements:

Data-driven business

Data and AI strategy elements

Keep your data and AI strategy up-to-date

It would be tempting to think that once you have outlined your data and AI strategy, the execution is simple and straightforward. However, nobody has a crystal ball that can predict the future, and even the best-made plans will not survive their first contact with reality intact. Therefore, we encourage you to build continuous experimentation and learning into your data and AI strategy execution. You need to identify the most critical assumptions that your plans are based on and proceed to test them swiftly. We recommend establishing a regular schedule for reviewing and fine-tuning your data and AI strategy at least annually, if not quarterly – it usually makes sense to synchronize the data and AI strategy review with the overall strategy review process.

Contact us!