The goal of this article is to help companies, CEOS, or CTOs understand how ready their organisation is to embrace or to start with AI. This article provides a set of stages for you to assess which stage your organization is at in regards to using AI or preparing to invest in AI. AI can provide your company with solutions for streamlining tasks and saving resources, time, or costs. As a starting place, please check out our Assessing Your Artificial Intelligence Readiness article, which looks at three elements that each organization should ask themselves when beginning to explore and seek AI solutions. This article addresses the three key stages of AI Readiness.

Stage 1: Exploration (Planning)

This is the earliest stage of the process. As an organization perhaps you are exploring what AI is and which value AI can bring to your business. Usually, if you are in this stage, it means your organization does not have AI solutions, but you may be interested in pursuing a first Proof of Concept (POC). (A POC is usually a pilot project that includes a design concept and business proposal.)

Once you shift from a general awareness of AI to targeted questions about problems and opportunities that AI can help address, that is where Sparkd.ai comes in. Sparkd.ai offers bespoke algorithms as AI solutions built uniquely around your systems, your problems, and goals.

If you have never considered AI or if you do not know the benefits of AI, perhaps a great starting place is asking your business these three questions:

• How can AI create value for my business?
• How are my competitors using AI?
• What can we do?

This is the stage where pilot projects are brainstormed and where plans are formulated to use AI to complete certain tasks within your business. It’s the starting place to lay out which use cases you want to target and improve within your organization. This stage builds the road map. The shift from the Exploration or Planning stage to the Experimentation stage occurs when AI solutions are seen as a benefit. When the potential of AI can be seen to address specific business functionalities and can be seen to create more business opportunities for you.

Stage 2: Experimentation

The experimentation stage begins testing hypotheses about what value can be created from specific AI solutions. This stage shows a willingness to experiment with AI and its effectiveness for your technological business cases. The organisation identifies which goals they would like to achieve with AI. Perhaps the first Proof of Concept (POCs) begins with the identification that an AI software vendor or a technical internal team is needed in order to support and carry out the deployment of AI technology. The POC should include a feasibility study and Application Programming Interfaces (APIs). (APIs act as a software intermediary that allows two various applications to communicate with the other.) You will want to set up AI for those use cases that have a high feasibility. It’s important to understand the potential of your data because AI can help you discover if solutions exist for a given problem. The organisation’s attention is focused on calculating risks and focused on topics, such as reliability, trustworthiness, and accountability.

• At this stage, you know:
  • what AI is.
  • why your business would need AI.
  • if you have already completed a POC.
  • that your competitors are using AI.

Stage 3: Stabilization

When your business has successfully deployed its first AI projects into production, usually pilots, which are used to obtain a measurable business impact, this is then the stabilization phase. You have built a production ready solution for your use case(s). (If the organisation has not yet matured in AI Governance, this stage will quickly discover those gaps.)

• At this stage:
  • AI is part of your current offering.
  • AI is marketed on your website.
  • You have a team of in-house specialists, and/or you have a partnership with an existing provider.

As the next step in this process, you can begin to scale your tasks and business by enhancing or improving efficiencies of your AI model or AI algorithm.

Conclusion

It is very important to know your organisation’s goals and objectives first. To see what use cases are of most importance to your organisation and to see where will be the most benefit and value in using AI for your output goals. Keep in mind the value that AI can bring to certain areas of your business, areas such as streamlining tasks, saving costs, time, or resources.

Sit down with your team and stakeholders to address output goals, growth strategy, and your competitive advantage against other businesses in the same industry. Brainstorm, answer questions, build a roadmap, and ultimately a Proof of Concept to begin your AI journey. Be mindful of your organizational goals and how to merge your use cases with AI.

Resources

Want a quick evaluation of your AI Readiness Level? Fill out this Google form to get your AI Readiness Level assessed by Gemmo; this is a free service we offer. One of our AI engineers will contact you with a bespoke assessment of your AI level.

Book a free AI clinic for an in-depth evaluation of your AI readiness.

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