In response to the growing need for strategic AI implementation, IT research and advisory firm Info-Tech Research Group has published its latest research, Build a Scalable AI Deployment Plan. The new resource aims to equip CIOs with the strategies and tactics required to effectively deploy AI technologies at scale and empower them to navigate the complexities of AI adoption with confidence and precision.
“Aggressively scaling artificial intelligence with the latest concepts and leading-edge technologies is an attractive ambition for many organizations,” says Andrew Kum-Seun, research director at Info-Tech Research Group. “However, rolling out AI as quickly and as broadly as possible often comes with costs that outweigh the benefits and may introduce cultural, security, and business operational risks and changes for which the stakeholders have no appetite. The lagging development of a good AI practice can further hamper the future returns of today’s investments.”
The firm’s research highlights several obstacles organizations face when deploying AI. Often, there exists a deficiency in implementation plans that are essential for CIOs to ensure the alignment of projects with AI initiative goals.
“The right AI initiatives help CIOs understand new AI technologies, their measurable impacts, and how these new technologies benefit their teams,” explains Bhavya Vora, research analyst at Info-Tech Research Group. “Appropriate initiatives also lend themselves to establishing good foundational capabilities and building the necessary relationships and collaborations to be successful in AI deployment.”
Info-Tech further underscores that CIOs should consider the following key elements when deploying AI:
- AI Solution Design: Break down the AI initiative into granular steps, such as building use case models and charting systems, data, and process flows, which serve as a critical component of the strategy. Identifying each step clarifies the initiative and lays the groundwork for seamless integration, thus accelerating AI implementation across various business functions.
- AI Capabilities: Establishing a frugal AI mindset enables prioritization of actionable progress over perfection. Organizations can effectively scale AI initiatives by concentrating on leveraging existing strengths and strategically addressing gaps. This approach emphasizes practicality and efficiency, facilitating meaningful advancements in AI implementation.
- AI Budget: Quantifying the impact of scaling the initiative involves conducting estimations to evaluate cost factors against the backdrop of risk and value potential. This systematic approach enables organizations to assess the feasibility of scaling AI initiatives while considering associated risks and potential value.
- Roadmap and Backlog: Crafting a roadmap and maintaining a prioritized backlog of AI initiatives act as a strategic compass, guiding the phased deployment of AI. By estimating and prioritizing the backlog of initiatives, organizations can assess the degree of effort and value, thus ensuring efficient allocation of resources and maximizing the impact of AI implementation.
The firm suggests it is imperative for CIOs and their organizations to position their AI deployment plan as a collectively owned and managed artifact focused on sharing, enabling, and continuously improving.
