Skip to content

Navigating the Disruption: Balancing AI Integration and Workforce Engagement Management

    By Jim Davies
    Analyst and Client Executive Partner

    With over 20 years of experience, Jim is a visionary analyst who has shaped markets and provided strategic advice to thousands of organizations. As the founder of groundbreaking frameworks such as the VoC and Workforce Engagement magic quadrants, and through his role as agenda manager for Gartner’s customer service research team, Jim has championed the elevation of customer experience and employee engagement. As an Executive Partner for Actionary, he continues his mission of driving impactful change in the industry.

    Summary

    Workforce Engagement Management (WEM) is fundamental for managing employee productivity and satisfaction. WEM evolved from its predecessor, Workforce Optimization (WFO) and represented a shift in focus from purely operational efficiency to a more human-centered approach, emphasizing employee engagement and work-life balance. However, the advent of Artificial Intelligence (AI) is disrupting this model, posing new challenges and opportunities for the WEM market. Landscape confusion and competing value propositions will significantly complicate procurement decision making.

    Actionary Take: Failure to balance AI benefit with WEM principles will harm employee satisfaction and productivity for the next three years.

    B2B CMOs Should Strategically Apply AI in Marketing to Drive Growth

      By Simon Harrison
      Analyst and Client Executive Partner

      Simon is an industry analyst who has authored over 30 Gartner Magic Quadrant notes as lead and with colleagues. He’s written important research as the Chief of Research advisor for Gartner. He continues to provide deep research and insights as an Executive Partner for Actionary clients and the industry..

      Summary

      Using Artificial Intelligence (AI) to improve personalization and customer journeys are leading priorities to drive revenue growth for B2B CMOs. However, the most widely available applications of AI in marketing are for more tactical and operational use cases such as lead scoring and propensity to buy. Access to data of suitable quality and a more holistic approach to AI infused in the marketing technology stack is key to realizing revenue growth. This research details three key success factors and how to achieve them to enable AI-powered revenue growth in Marketing.

      Actionary Take: Unless Marketing leaders change their approach to martech stack innovation, and address the fragmented data reality, they will fail to realize AI-empowered growth.