Four steps to building a good AI base

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If a business owner is unsure about how AI can benefit their business, there are many facets to consider before making any decisions. These considerations can help business owners understand the potential impact of AI on their operations and determine whether investing in AI is the right choice for their specific business. Here are four important considerations:

Business Objectives and Needs: The first step is to clearly define the business’s objectives, challenges, and pain points. Determine what areas of the business could benefit from automation, optimization, or improved decision-making through AI. Whether it’s enhancing customer service, streamlining operations, optimizing supply chain management, or personalized marketing, aligning AI applications with business needs is crucial.

Competitive Landscape: Research how competitors are utilizing AI technology in their operations. Understanding the AI landscape in your industry can help identify potential advantages or risks of falling behind. By staying informed about industry trends, a business owner can make informed decisions about where AI may have the most significant impact.  As of today, this may be a small list, but it will grow, and it’s important to keep this in focus.

Governance and Quality: Like all process and data systems, good governance and ownership allow trust to build.  AI systems rely heavily on trust to be successful (trust of execution, trust in the data, trust in the decisions made, etc.).  Well-implemented governance also affords the ability of the business to evaluate and maintain the quality, availability and use of the solution. Problems such as poor data quality can lead to inaccurate AI outcomes, which can lead to a feeling of “not being ready”. Governance processes can remedy that.  Good governance can allow small forays to be proven whilst larger data and process needs are identified. It can allow an organisation to start sooner and gain benefits faster.  Other governance considerations include the need to consider data privacy and security concerns, as handling sensitive customer information requires compliance with relevant regulations like GDPR or CCPA.

Feasibility and Implementation Costs: Once ideas become more real, it is important to assess the feasibility of integrating AI solutions into the business. Consider the required infrastructure, data collection, and analysis processes. There may well also be a change management stream to embed, re-train or include new solutions and ways of working into teams and roles.  AI implementation should not be viewed as a one-time fix but rather an ongoing process that evolves with the business. Being able to integrate and modify AI solutions as needed ensures the business remains competitive in the long term.

Remember that the decision to adopt AI does not mean a rushed proliferation of low-value, ungoverned outcomes. It can mean identifying concepts and taking them forward.  We can help with the “Art of the Possible” or even piloting small AI projects or conducting proofs of value.