Are you an artificial intelligence cub or lion?

Are you an artificial intelligence cub or lion?

Assess and advance your organisation’s AI capability using Gartner’s AI Maturity Model, a useful framework for organisations looking to understand and implement AI.

Assess and Advance Your Organisation’s AI Capability Using Gartner’s AI Maturity Model

Artificial intelligence (AI) is transforming the world of business, creating new opportunities for innovation, efficiency and competitive advantage. However, not all businesses are equally prepared to embrace AI and leverage its full potential.

This begs the question, is your organisation ready, or even capable, for the AI future?

In this article, we will explore Gartner’s AI Maturity model, a useful framework for assessing your organisation’s current level of AI capability and adoption.

Gartner’s AI Maturity Model

Gartner’s AI maturity model is a framework that helps data and analytics leaders assess their organisation’s current and desired state of AI adoption and implementation.

The model segments organisations into five levels of maturity regarding their use of AI: Awareness, Active, Operational, Systemic and Transformational. Each level represents a different degree of AI integration, value and impact across the organisation’s processes, products and services.

By understanding where your business stands in terms of AI adoption, you can identify the gaps and challenges you need to overcome and the best practices you need to follow to move towards higher levels of maturity.

Whether your organisation is a growing cub, starting to first explore generative AI tools like ChatGPT, or a roaring lion with a fully-fledged AI center of excellence, this is a useful framework for understanding and charting the best course of action for your context.

The Five Levels of AI Maturity

According to Gartner, the five levels of AI maturity are:

  1. Awareness: Companies at this stage know about AI but haven’t quite used it yet. They may have ideas about how to use AI in their businesses but not strategies.
  2. Active: Companies at this stage are experimenting with AI informally. They may have implemented a few models and are playing with AI.
  3. Operational: Companies at this stage have adopted machine learning into their day-to-day functions. They likely have a team of ML engineers and have the ML infrastructure set up.
  4. Systemic: Companies at this stage have integrated AI into multiple business processes and are using it to drive business value.
  5. Transformational: Companies at this stage have fully integrated AI into their processes and are using it to drive transformational change.

Using the Maturity Model to Assess Your Current Maturity

To use the AI maturity model to assess your business, you can ask yourself some questions such as:

  • What are the main goals and objectives of using AI in your business?

Cubs may have the goal of exploring and understanding the potential future impact of AI on their organisation, while lions would seek to fully integrate intelligence into their products and services to drive growth and transformation.

  • What are the current use cases and applications of AI in your business?

Does your organisation currently use AI in any aspect of its strategy and operations? If so, how effectively is it being utilised and is it driving the business impact envisioned? For the eager cubs, what examples of industry leaders, peers and competitors might they draw inspiration from to define practical use cases and meaningful applications.

  • How do you measure the impact and value of AI in your business?

    AI can have a significant impact and value, depending on how you define, measure, and compare it. You need to set clear and measurable goals for your AI projects, such as improving efficiency, accuracy, revenue, cost, customer satisfaction, employee engagement, or social impact. This then needs to map onto relevant metrics and indicators to track and evaluate the performance and outcomes of your AI projects: time for efficiency, error rate for accuracy, conversion rate for sales and so on.

    Fortunately, there are useful models and frameworks that cubs and lions alike can use to guide the assessment process, such as the AI Value Canvas, the AI Impact Framework, or the Responsible AI Framework.

  • What are the skills and capabilities of your staff regarding AI?

    To assess the skills and capabilities of your staff regarding AI, you need to consider their AI literacy, AI proficiency, and AI training and education. You need to evaluate how familiar, skilled, and experienced they are with AI concepts, tools, and platforms, and how accessible and available AI learning resources are for them. Depending on your evaluation, you can determine if your staff are at the cub or lion stage of the maturity model.

    For example, a cub might have staff who are unaware or confused about AI, who have no or limited skills in using AI tools and platforms, and who have no or scarce access to AI training and education resources. A lion would have staff who are knowledgeable and confident about AI, who have high or expert skills in using AI tools and platforms, and who have abundant or tailored access to AI training and education resources.

  • What are the tools and platforms you use to develop and deploy AI solutions?

    To assess the tools and platforms you use to develop and deploy AI solutions, you need to consider their quality and suitability, and their integration and interoperability. You need to evaluate how reliable, efficient, effective, and supportive they are for your AI projects, and how well they work with your existing infrastructure and processes. Depending on your evaluation, you can determine if your tools and platforms are at the cub or lion stage of the maturity model.

    Is your organisational data stored in disparate excel sheets, on Mpumi and Steve’s hard drives? Probably a cub.

    Have a clear data pipeline, with data streams feeding into a unified, cloud-based data lake? We see you, Mufasa.

Of course, this list of questions is by no means comprehensive. The model itself may not capture the full complexity and nuance of your organisation’s AI journey. The pace of technological change also means that the model itself may need to be updated regularly to reflect the latest developments in the field.

Lions and cubs alike would still need to consider the questions of ethics and the unique risks and challenges involved with a particular implementation project. By answering these questions aligned to the Gartner model, however, you can get a sense of which level of maturity best describes your current state of AI adoption. You can also benchmark yourself against other businesses in your industry or sector and see how you compare and then start to chart a strategy to get ahead.

Advancing your AI maturity is not just a matter of keeping up with the latest technology trends. It is also a matter of staying ahead of the competition and creating value for your customers, employees, and stakeholders. AI adoption has more than doubled since 2017, with 50% of businesses reporting using it in at least one area as of 2023. Make sure that you aren’t falling behind.

Ready to Take Your AI Maturity to the Next Level?

If you are interested in learning more about how to assess and advance your business’s AI maturity, you might want to check out Auxo Digital’s AI for Execs course. This course is designed for business leaders who want to understand the fundamentals of AI, its applications and implications, and how to develop and implement an AI strategy for their organisation.

Sign up here: AI For Executives | Auxo Digital