Unlocking Gen AI Potential in IT

In this episode of the “Business Excelleration^® Podcast,” Anthony Snowball, Kyle Robichaud and Joe Nathan discuss the tangible advantages businesses are experiencing, while also addressing the critical ethical considerations of adopting generative artificial intelligence (Gen AI). They also examine the pivotal role of boards and executives in setting pragmatic expectations and crafting effective AI strategies for sustainable growth.

Welcome to The Hackett Group’s “Business Excelleration Podcast,” where week after week we hear from experts on how to avoid obstacles, manage detours and celebrate milestones on the journey to world-class performance. This episode is hosted by Anthony Snowball, leader of The Hackett Group’s AI go-to-market and AI/IP innovation. Today’s conversation focuses on the five steps to accelerate your journey using Gen AI technology. Anthony is joined by Kyle Robichaud and Joe Nathan, senior leaders within The Hackett Group’s IT practice and AI consulting.

To begin, Anthony highlights the buzz around AI for business excellence from both supply (vendors and platforms) and demand (enterprise and consumer) perspectives. The Hackett Group’s recent study on Gen AI revealed a 44% capacity creation, which can be leveraged to enhance productivity or reduce costs. Beyond capacity creation, Gen AI offers exponential benefits such as creating new revenue opportunities exemplified by the accelerated drug development process in life sciences. Then, Kyle provides examples of opportunities and benefits that clients are realizing from Gen AI from the information technology (IT) sector. These include service desk ticket resolution and automated testing. AI significantly improves service desk efficiency by resolving tickets without human intervention, allowing IT staff to focus on higher-value tasks. In testing, AI generates and executes test cases faster than traditional methods, enhancing productivity. In development, AI can assist in code generation though proper usage and understanding of AI-generated code are crucial to avoid misalignment with specific environments.

Next, Kyle and Joe discuss the challenges that prevent IT organizations from fully unlocking the power of Gen AI. Data quality emerges as a major issue, emphasizing the need for timely, accurate and well-managed data. Legacy applications pose another challenge because they lack embedded AI capabilities. Security concerns, particularly with closed AI models, and the inability to backtrack decisions create additional liabilities. Training on AI tools is critical; without proper training, suboptimal processes and outcomes can arise.

Kyle introduces The Hackett Group’s five-step approach for IT executives and practitioners to use AI responsibly and effectively. The first step is educating and informing the team about Gen AI, setting realistic expectations about what AI can and cannot do. This strategic approach ensures that AI is used where it can provide the most value, avoiding suboptimal or ineffective applications. Second, organizations should understand current challenges and recognize the existing hurdles to avoid unnecessary complications. Third, they should examine specific use cases to evaluate how Gen AI can impact specific business processes. Fourth is assessing organizational readiness to ensure data quality, skill sets, governance and infrastructure are in place. The final step is to develop a prioritized Gen AI road map specific to your organization.

The discussion shifts to the importance of a top-down approach in deploying Gen AI. Leaders must be cautious not to get swayed by the hype around specific use cases, but instead focus on strategic goals and the overall potential returns of AI. There is also a strong emphasis on having robust data quality, governance and ethical considerations in place. For companies to become AI-ready, they must address practical concerns such as data governance and ethical issues. Ensuring data quality and availability is fundamental before integrating Gen AI platforms. Effective data governance policies, including data classification and compliance, are essential to manage what data can be shared openly.

Time stamps:

0:49 – Welcome to this episode hosted by Anthony Snowball.

1:10 – The potential of Gen AI.

3:13 – Real-world applications and benefits of Gen AI.

6:22 – Challenges in implementing Gen AI.

11:44 – The five key steps to successfully leverage Gen AI.

21:17 – How to implement this strategy into AI adoption.

23:02 – Training and ethical concerns.

25:04 – Thanks to Kyle and Joe for joining us on this episode.