Building an AI culture

1. Building an AI culture

We have mastered the art of framing business problems and determined which ones need AI. Next, let's discuss an important part of a successful AI strategy that goes beyond technology - cultural change.

2. Disruption to status quo

AI is often compared with groundbreaking inventions like electricity, the printing press, and the steam engine, highlighting how it has transformed the way the world used to run. For business leaders, AI is a disruptive force that prompts the need to make swift investments to stay relevant and maintain a competitive edge. This urgency to revolutionize the current working methods can sometimes lead to resistance and a wish to continue with the status quo.

3. Disruption = change

Disruption means change is in order, and change signifies transitions by its very nature. These transitions require moving on from established norms and practices that often bring uneasiness. A successful AI transition necessitates a profound cultural shift for leaders and their teams, compelling them to think beyond the usual ways of running businesses.

4. Periodic milestones

Let us first discuss how leaders need to approach AI transformation: Instead of setting one big overarching goal that promises to demonstrate the value of AI at the final stage of project completion, it is essential to set up intermediate milestones. It includes showing value creation at every stage and taking timely feedback. For example, when using AI for operational efficiencies, creating a chatbot is the first step to free up the time spent answering redundant questions and directing it in complex problem-solving.

5. Phase-wise transformation - no moonshot

AI initiatives are better equipped to solve problems with increasing complexity by addressing feedback at every phase. Each phase has its sub-goals collectively directed towards the overarching goal. For example, the first phase of the AI chatbot might focus on efficiently handling frequently asked questions before advancing to tackle more complex queries. The phase-wise structure is a win-win approach for the business and technical teams. It preempts last-minute surprises, allowing timely assessment of periodic results and any necessary recalibration.

6. Setting the right expectations upfront

AI is probabilistic by nature, so it won't be able to work at 100% accuracy. Hence, it is essential to set realistic benchmarks for success. In the case of chatbots, it is essential for the business to set practical expectations, which could be measured by accuracy, such as how many user queries are correctly addressed, or the time taken per query, such as how long the chatbot takes to understand the user query correctly.

7. Understand the iterative nature of AI

AI projects are exploratory and often necessitate innovation, which is challenging to time-box. Hence, it is essential to be aware of the change in the project's scope and extended timelines.

8. From leaders to teams

Great, the leaders have initiated the AI culture, ready to trickle down to the teams. So, what does it require to lead a culture change successfully? Leaders must ensure that their teams accept and actively participate in the transformation. A team’s willingness to innovate depends on a culture that promotes trying newer things and does not penalize failing.

9. AI strategy comes from positive culture

A strong AI strategy involves creating a positive culture where employees are not judged or punished for attempting risky projects, knowing the bleak chances of success. The idea is to keep collating the learnings from what did not work until it starts to work. It is worth noting that normalizing failures takes courage. Hence, it is essential to glorify failures as opportunities.

10. Let's practice!

We have learned the role of building a strong AI culture to empower the AI strategy. It is time to practice the risk-taking ability.

Create Your Free Account

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.