Why data readiness is key for successful AI deployments
By David Griffith (pictured), Chief Data Architect at Atturra
As organisations formulate strategies to extract value from artificial intelligence (AI) tools, many are coming to the realisation that data readiness needs to be a key factor.
The reason is that AI’s potential is directly tied to the quality, availability, and governance of data. Without a strong data foundation, organisations risk navigating uncertainty and failing to harness the full potential of AI.
To achieve this, however, often means a mindset shift. Rather than looking at AI from a technology perspective, strategies need to be designed and implemented using a business-led approach.
This will require increased collaboration between business and technology teams which will allow data strategies to be seen through the lens of business objectives and aligned closely with organisational goals. Rather than simply a change of tactics, this actually represents a complete rethink of how data is integrated and utilised in business processes.
Also required will be an innovative mindset. This will ensure that data is treated with the flexibility and creativity of a startup which, in turn, can lead to groundbreaking results.
Before an AI deployment project is undertaken, a thorough data readiness assessment should be undertaken. Such assessments evaluate the various aspects of an organisation’s data capabilities, including analytics, governance, and cultural readiness. This will ensure a well-prepared journey into the world of AI.
As AI tools continue to evolve and extend their capabilities, new leadership will also be required, particularly from those people heading up information and technology teams. These leaders will need to adopt a mindset that embraces innovation, agility, and a deep understanding of business needs, thereby aligning data operations closely with the strategic objectives of the organisation.
This shift represents a departure from traditional data management methods. It is about nurturing an agile, customer-centric, and innovative data-driven culture that extends across an organisation. Business leaders will need to constantly view data not just as a resource but as a vital component driving growth, innovation, and competitive advantage.
Extracting business value from AI
When data readiness and business-led strategies are at the forefront, organisations are best placed to gain maximum benefit from the deployment and use of AI tools. Rather than being a technical novelty used only by IT teams, they can become invaluable aids that significantly streamline business processes and increase productivity.
There are some key factors that business leaders need to keep in mind when undertaking AI-based projects and strategies. They are:
- Take the right approach: It is vital that business leaders focus on developing data-driven AI projects that take a business-centric approach. This will maximise the value that is achieved.
- Embrace dynamism: Even large businesses will need to adopt a startup culture when it comes to the way data is managed and used. Traditional approaches and methods will need to be carefully reviewed and adjusted as required.
- Integrate data operations: Rather than being treated as a separate resource, data operations will need to be folded in as a core component of business strategy. This will ensure the results of the project are aligned with expectations.
- Maintain a customer focus: When data products and services are being developed, it’s important that they are closely matched with customer needs and organisational goals. Any failure to do this will lead to suboptimal results.
- Focus on strategic objectives: Throughout all AI projects, senior managers need to ensure data quality measures are aligned with their organisation’s strategic objectives and value propositions. Taking a long-term perspective will increase the benefits that are achieved.
For AI projects to deliver the maximum impact to an organisation, it is vital that data readiness remains front and centre. AI tools must be able to work effectively with diverse datasets, both structured and unstructured, and adapt to new forms of data.
Senior managers will need to recognise the importance that chosen AI systems are able to seamlessly navigate through a spectrum of data types and be continually adaptable. The ability of AI to evolve and adeptly handle new forms of data is not just a technical requirement but a strategic asset.
This ability will enable organisations to glean insights from the wealth of information they have available, thereby fostering a more comprehensive and informed decision-making process.
AI tools will continue to evolve and expand their capabilities at a rapid rate. By taking steps to ensure their data resources are available and used correctly, organisations will be best placed to benefit from these advances in the future.