×
With AI adoption pacing is crucial, Gartner keynote emphasizes
Written by
Published on
Join our daily newsletter for breaking news, product launches and deals, research breakdowns, and other industry-leading AI coverage
Join Now

AI implementation strategies: Gartner’s insights for businesses: Gartner analysts Mary Mesaglio and Hung LeHong presented key strategies for building successful AI stacks and pacing AI implementation during the Gartner IT Symposium/Xpo 2024.

  • The pressure on CIOs to execute AI strategies is increasing, with 57% of them tasked with creating such strategies according to a Gartner survey.
  • Gartner analysts outlined two distinct implementation paces: “AI-steady” for organizations with modest AI ambitions, and “AI-accelerated” for those with larger ambitions or operating in industries being reinvented by AI.
  • A Gartner survey revealed that employees saved an average of 3.6 hours per week using generative AI, although productivity gains vary significantly across different use cases and organizations.

The AI ‘sandwich’ model: A framework for implementation: Mesaglio and LeHong introduced a visual concept of an AI “sandwich” to help organizations understand and structure their AI implementation strategies.

  • The top and bottom layers of the sandwich represent structured and unstructured data, as well as various AI types and applications.
  • The crucial middle layer consists of trust, risk, and security management (TRiSM) technologies, which are essential for responsible AI deployment.
  • AI-steady organizations typically govern their AI implementations through human teams and committees, while AI-accelerated organizations incorporate additional TRiSM technologies to manage their more ambitious AI initiatives.

Addressing employee wellbeing in the AI era: The analysts emphasized the importance of managing the human impact of AI implementation, highlighting a significant gap in current business practices.

  • Only 20% of CIOs are proactively addressing employee wellbeing concerns related to AI impacts, indicating a need for greater attention to this aspect of AI adoption.
  • The presenters stressed the importance of managing behavioral outcomes resulting from AI implementation with the same rigor as technology and business outcomes.

Productivity gains and implementation challenges: While AI offers significant potential for improving productivity, the actual benefits can vary widely across different use cases and organizations.

  • The average time saved by employees using generative AI (3.6 hours per week) suggests promising productivity gains, but also indicates that results may not be uniform across all implementations.
  • Organizations need to carefully assess their specific use cases and potential benefits when planning AI adoption to ensure realistic expectations and maximize returns on investment.

Tailoring AI strategies to organizational needs: The distinction between AI-steady and AI-accelerated approaches highlights the importance of aligning AI implementation strategies with an organization’s overall goals and industry context.

  • Companies in rapidly evolving industries or with ambitious AI objectives may need to adopt an AI-accelerated approach to remain competitive and capitalize on emerging opportunities.
  • Organizations with more modest AI ambitions or operating in less AI-disrupted sectors can benefit from a measured AI-steady approach, focusing on incremental improvements and careful integration of AI technologies.

The critical role of trust, risk, and security management: The emphasis on TRiSM technologies in the AI sandwich model underscores the growing importance of responsible AI deployment.

  • As AI systems become more prevalent and influential in business operations, ensuring their trustworthiness, managing associated risks, and maintaining robust security measures become paramount.
  • Organizations adopting more aggressive AI strategies need to invest in advanced TRiSM technologies to effectively manage the increased complexity and potential risks associated with extensive AI integration.

Balancing technology and human factors: Gartner’s analysis points to the need for a holistic approach to AI implementation that considers both technological and human aspects.

  • While the technical aspects of AI implementation are crucial, organizations must also focus on managing the impact on employees and organizational culture to ensure successful adoption and sustainable benefits.
  • The low percentage of CIOs proactively addressing employee wellbeing in relation to AI impacts suggests an area for improvement in many organizations’ AI strategies.

Looking ahead: Strategic considerations for AI adoption: As businesses continue to navigate the rapidly evolving AI landscape, several key considerations emerge from Gartner’s analysis.

  • Organizations must carefully assess their AI readiness and objectives to determine the most appropriate implementation pace and strategy.
  • Investing in robust TRiSM technologies and practices will be essential for managing the increasing complexity of AI systems and ensuring responsible deployment.
  • A greater focus on the human aspects of AI implementation, including employee wellbeing and behavioral outcomes, will be critical for long-term success and sustainable AI integration in the workplace.
Proper Pacing Essential for AI: Insights From Gartner Keynote

Recent News

AI agents and the rise of Hybrid Organizations

Meta makes its improved AI image generator free to use while adding visible watermarks and daily limits to prevent misuse.

Adobe partnership brings AI creativity tools to Box’s content management platform

Box users can now access Adobe's AI-powered editing tools directly within their secure storage environment, eliminating the need to download files or switch between platforms.

Nvidia’s new ACE platform aims to bring more AI to games, but not everyone’s sold

Gaming companies are racing to integrate AI features into mainstream titles, but high hardware requirements and artificial interactions may limit near-term adoption.