CIO Digital Enterprise Forum Takeaways: A Conversation on AI Implementation

May 22, 2024 | min read

CI&T

We recently participated in the CIO Digital Enterprise Forum, where key tech industry figures gathered to discuss the opportunities and challenges of AI implementation. During the event, our VP of technology, Mark Rodseth, presented his valuable insights on driving successful AI adoption for future growth and scalability.

A key theme emerged: show, don't tell. Mark and other speakers emphasised the importance of showcasing AI's power through practical applications. This builds trust and empowers workforces to leverage this transformative technology.

Below are some of our top takeaways:

1. Mark Rodseth’s learnings and guidance: Show, don't tell

In his presentation, Mark Rodseth delved into how becoming an AI-first organisation is imperative for a company’s success and survival. He provided detailed guidance on a Generative AI project lifecycle and the steps to getting started: Execution, Development, Training, Strategy, and Communication.

Similarly to other speakers, Mark also reinforced the concept of "showing, not telling" when it comes to AI implementation. By demonstrating the power of AI through practical applications, organisations can build trust and empower their workforce to leverage the technology.

2. Measuring AI’s impact

Measuring the impact of Generative AI adoption within an organisation is critical to understanding the impact on efficiency, cost reduction and innovation. By understanding the areas where Generative AI makes a difference, an organisation can tailor their adoption strategy and investment to focus on those areas and give them a greater competitive advantage. Measuring is difficult to get right but tackling this as part of a Generative AI strategy, which will create an empirical baseline you can work from and ensure you are investing in the right place.

3. Demystifying AI for leaders

Educating senior stakeholders about AI's role in propelling organisations forward was a recurring theme. In a discussion about gaining buy-in from board members on Generative AI implementation - a topic our EVP & Partner Solange Sobral recently explored - speakers highlighted the need to address C-suite’s “fear of missing out” and their anxieties on AI rampaging their organisations with job displacement, privacy issues. The reality is that while AI will undoubtedly impact organisations, it won't revolutionise them entirely. A company's core values and objectives will remain constant. Transparency is key.

4. Building on existing knowledge: AI isn’t new

Generative AI (like large language models) can create the impression that AI is entirely new. However, machine learning has been around for years. Organisations can leverage their with existing knowledge by introducing machine learning tools and transforming processes to inform their AI implementation strategies.

5. Proving the value of AI

Mark, along with other leaders, discussed the importance of proving the value of AI’s potential by creating small proof-of-concept (POC) projects that showcase AI's capabilities and limitations within an organisation. They also advised that success stories can be powerful tools for getting buy-in and investment for future initiatives.

6. Empowering the workforce, with empathy

AI should be positioned as an empowering tool, not a threat. Training and education are critical to ensure employees feel comfortable and confident working alongside AI. Empathy and a focus on diverse skill sets are essential in fostering a collaborative work environment where AI complements human capabilities.
AI is ultimately about people. Leaders need to consider the human impact of AI implementation, including potential decision fatigue and the need for clear policies.

7. Are we considering AI’s impact on the environment?

Green Web Foundation’s Hannah Smith shed light on the environmental impact of AI, offering advice for fostering more environmentally friendly AI practices. She addressed how major technology tech companies, including Microsoft and Google, have faced scrutiny on their failing green targets largely due to their focus on developing AI tools. Ultimately, while AI offers vast potential, its development and use can be computationally expensive, with growing energy use from data centres, raising concerns about its footprint.