How to assess your AI readiness with 50 questions

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By now, everyone has recognized that we are in an AI hype. Again. It is probably the fourth since Joseph Weizenbaum developed the famous ELIZA, a natural language processing program that was intended to explore communication between humans and machines.

In the early nineties we saw another wave when we saw the first neural networks; in the tens of this century, we saw machine learning making strides and now …

Now we have generative AI.

And every vendor – and buyer – jumps on it, often thinking of drastically improving business and employee performance – or replace some employees with technology – and of enjoying the ultimate competitive advantage.

Nothing could be farther from the truth. Adapting and using AI tools gives a temporary advantage at best.

Why temporary? Temporary, because technology is nothing that the competition cannot use. In fact, they will do the same and with that, any, or at least most, competitive advantage gets leveled again.

And why at best?

Because you might not get an advantage at all, for several reasons. Chief of them is missing corporate readiness. AI can be a very helpful tool, but it is a tool, that needs an organization to be prepared across several dimensions. Regardless of how these dimensions are laid out in detail, they include Strategy and leadership, infrastructure, people, culture, governance and last, but not least, data.

Not being prepared in one or more of these dimensions can greatly diminish the projected benefits of adopting AI technology. A simple yet obvious example would be the employees being hesitant to use the provided tool if they feel that their positions are endangered by it. A planned for increase in productivity will then be lower than expected or might not get realized at all. Or lacking strategy, which will lead to unfocused and probably redundant deployments. A third example would be incomplete or, worse, inconsistent data; this does lead to unreliable outcomes.

AI readiness

Here are the key questions you need to answer to assess your company’s AI readiness. The answers to these questions give you detailed into implementing your own road to effective and efficient use of AI.

Strategy and leadership

Is there a clearly defined AI strategy?

Does this strategy have measurable objectives?

Do you have identified business cases?

Is there a clearly defined owner of the AI strategy?

What is the priority of the AI strategy compared to other strategies?

Is there sufficient executive support for this strategy?

Is a budget matching the strategy’s importance allocated that allows for sustainable funding of AI deployment projects/initiatives?

Are sufficient people assigned to the strategy to execute it?

Are sufficient resources allocated to the strategy to execute it?

Infrastructure

Is the compute power available to use and run an AI system (if run in the own network)?

Is your IT infrastructure flexible enough and capable of scaling to meet changing demands of AI workloads?

How efficiently can compute resources be allocated between different workloads to meet demands?

Do you have fast and low-latency connections in your data center?

Are the connections between the different cloud systems secure?

Is the company’s cyber security set up to deal with additional systems and data?

How do you ensure the protection of data that is utilized in AI models?

How do you manage access to AI systems and data sets they work with?

How sophisticated is your analytics tool set to work with AI-related datasets?

How well are your analytics tools integrated with data sources and AI platforms used?

People

What change of job security do the affected employees perceive?

Do employees perceive AI as useful for their work?

Do you know which skills do I need to help employees build?

Do you have a sufficient number of employees with the skills needed for successful AI deployments?

In particular, how proficient is your analytics team to leverage analytics tools for AI projects?

Do you have a training plan established to upskill existing employees in AI-related competencies?

Do you have a plan to hire people with matching skills?

Culture

Is a change management plan in place?

Is the company open to the changes that caused by the usage of AI systems?

 Is the company’s top management open to the changes that caused by the usage of AI systems?

Is the company’s middle and lower management open to the changes that caused by the usage of AI systems?

Are the company’s non-management employees open to the changes that caused by the usage of AI systems?

Are changes actively communicated by the management?

Governance

What is the level of awareness about global and regional data privacy regulations including data sovereignty?

Are processes in place that enable the adherence to (changing) regulations?

Is an ethical use of AI policy in place?

Is it ensured that corporate data cannot leak into external systems, i.e., that data protection and data privacy are ensured?

Does the company have a risk management strategy in place that covers the use of AI?

How prepared are you to address a data breach or privacy violation?

How do you ensure that data is stored and processed in alignment with different local data sovereignty laws?

Ho do you handle cross-border data transfers to ensure they adhere to data sovereignty laws?

What is the level of awareness regarding biases and toxicity in results of AI systems?

Do you have processes and mechanisms in place to proactively prevent biases and toxicity in your AI systems?

Do you have processes or mechanisms in place to detect and remove biases and toxicity from your AI systems?

Do your AI systems offer explainability features to ensure transparency of its inferences?

Data

Does your company have sufficient data to train the AI system?

Is there enough data to test the AI system?

Is the data clean enough to enable reliable results?

Do you have mechanisms and processes to keep your data clean?

Do you have a consolidated data repository or a semantic layer on top or your data?

How accessible is your data for AI systems?

What next?

Answer above questions for yourself – or even better, take a readiness assessment – to find out where you are in relation to effective and efficient use of AI technologies across these crucial dimensions.

But be serious about it. There is nothing worse than lying to oneself. Doing so will only lead to misguided investments, followed by disappointing results.

Plan the next steps of your AI initiatives based on the outcome of this assessment and get on a sustainable road to using the increasing power of AI systems.

Need help? Talk to me!

Republished with author's permission from original post.

Thomas Wieberneit

Thomas helps organisations of different industries and sizes to unlock their potential through digital transformation initiatives using a Think Big - Act Small approach. He is a long standing CRM practitioner, covering sales, marketing, service, collaboration, customer engagement and -experience. Coming from the technology side Thomas has the ability to translate business needs into technology solutions that add value. In his successful leadership positions and consulting engagements he has initiated, designed and implemented transformational change and delivered mission critical systems.

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