How would you rate the level of AI adoption in your company? That was the precise polling question posed to our panel participants during the “Pathway to AI Adoption” session at the 16th CIO Executive Summit 2023, hosted by MIG Events. An overwhelming majority of over 60% of the audience rated their company’s AI adoption as 4 or lower on a scale of 1 to 10 (highest).
On behalf of DaLa – Data Literacy Association (#DaLa), I moderated a panel with 3 outstanding IT leaders including Andy Chun #Prudential, Dan Wong #MTR (former) & Francis Ng #OCBC. We had a fruitful discussion on the AI adoption and lesson learned in the journey. We also talked about how to generate and prioritize AI experiments and use cases. Appreciate Andy, Dan & Francis for their valuable insights.
My 3 key takeaways:
1. “Push and Pull” Strategy –
Emphasize Strategic Vision and Empowerment:
To foster a successful AI and Data culture within a company, it is crucial for the leadership team to adopt a dual approach of “Push” and “Pull.” The “Push” aspect involves the leadership team strategically and sustainably driving the integration of AI and Data throughout the organization, rather than treating it as a series of isolated projects. On the other hand, the “Pull” aspect entails empowering business users with the necessary data literacy, innovative mindset, and customer centricity to initiate AI and data analytics use cases. Senior management’s support and buy-in for the AI and Data strategy play a vital role in facilitating this process.
2. Shifting Priorities at Different Stages:
Throughout the AI adoption journey, it is important to recognize that different stages require different priorities. In the initial stages of low AI adoption, the focus of the Chief Information Officer (CIO) typically revolves around establishing a robust data infrastructure. Once the data infrastructure is in place, the CIO’s attention should shift towards driving business value and empowering users at the forefront of operations to identify and drive AI-driven use cases. This transition ensures that the organization maximizes the potential benefits of AI and Data by aligning technology with business objectives.
3. Establish Effective Data Governance:
As AI adoption reaches higher levels, the associated risks also increase. Therefore, it becomes imperative for companies to proactively implement robust data governance practices early on to mitigate potential issues. An effective data governance framework ensures that data quality, privacy, security, and compliance standards are upheld, minimizing the likelihood of serious problems arising from AI and Data initiatives.
At DaLa, we eagerly anticipate collaborating with experts in AI and Data, as well as business users, to co-create additional value for our customers using the wealth of data assets at our disposal.
#DataLiteracy #DataInfrastructure #DataCulture #DataMindset #DataGovernance #ResponsibleAI #AIAdoption #CIO #CDO #CTO #CEO
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