AI Talk: Leading the rollout of AI tools across your organisation

On 12 November 2024, AI Talk host Kevin Craine was joined by Ronald Gerlach, Chief Marketing Officer, Gaubert Oil Company; Jamie Grabert, President/Co-Founder, The Consultancy Group; and Yemi Oluseun, Programme Director - Business Transformation Strategist, The Change Hive.

Views on news 

Whenever new technologies emerge rapidly and related regulations are drawn up, organisations too must adapt quickly though also with a longer-term view. To deploy AI in a trustworthy and sustainable way, business leaders must manage the broad spectrum of risks in a pragmatic manner. A recent Deloitte survey has found that only 23% of respondents rated their organisations as highly prepared in the area of risk and governance for AI. AI compliance is getting trickier, especially with the new  EU law on ethical AI use in force. As a result of the impact AI is already having on politics and business, other countries are likely to follow suit. Prior to any AI deployment, it’s important to map out existing processes.

 

Prioritizing use cases

Start deployment with low-hanging fruits that automate repetitive, mundane task, then go on to enhancing customer experience with chatbots that can do personalised recommendations. The risk of bias can have very serious consequences in critical sectors, such as in criminal justice and healthcare. There is also the risk of data misuse and breaches. The cost of AI can be prohibitive, but price is not the only cost aspect. You can lose out on the benefits if you have a skewed view of what AI is capable of or suited to. In both white and blue collar jobs, employees will need to learn to use AI to stay competitive. You must train your AI and your people together simultaneously. It should be the shared responsibility of employers and employees to upgrade AI skills. The steps that businesses should take are (1) identifying where AI can make the most value (2) engaging stakeholders early (3) prioritize the availability of high quality relevant data. Cross-departmental collaboration is key to success. The business needs an AI champion who can engage in honest conversations with employees.

 

You also need to establish at the start how you’re going to monitor success and make corrections when needed. Centres of Excellence that include technologists, executives and process owners. The problem is that many businesses still think of departmental silos and create an isolated AI team. In applications such as identifying leads, the number of closed deals can be a good metric. Always align AI implementation metrics with the KPIs of your department. It’s also important that you keep honest and transparent about the use of AI as a business, which can also differentiate your brand from the others. Employees should also be empowered to report any ethical concerns regarding the use of AI.

The panel’s advice

• Prioritize use cases. Start AI implementation with ones that aren’t intrusive in areas which aren’t heavily regulated.
• AI is not a set it and forget it solution. You have to evaluate the system for performance, accuracy and ethical criteria on an ongoing basis.
• As a first step, ensure the accuracy, security and accessibility of data.