And time for some big ideas.
Harvard Business Review asks – if Trust is So Important, Why Aren’t We Measuring it? The article highlights that while leadership trust is crucial for positive organizational outcomes, many companies struggle to measure it effectively. Interviews with over 70 senior leaders revealed that while all agreed on the importance of trust for employee performance, customer loyalty, and innovation, most could not identify any definitive metrics for assessing it. Some suggested using proxy measures like Net Promoter Score or employee engagement surveys, but many deemed trust too subjective and “soft” to quantify. This raises an important question: if trust is foundational to successful leadership, why isn’t there a robust framework for measuring it?
From Information Week, Mary E. Shacklett, President of Transworld Data , writes how the integration of artificial intelligence and automation is poised to significantly impact employment within the sector, particularly through potential layoffs. As organizations increasingly adopt AI-driven solutions for operations such as network management and help desk services, the role of IT staff may shift dramatically. Automation can streamline processes, reducing the need for human intervention in routine tasks; however, jobs in areas like security and systems programming are expected to remain stable due to their complexity and the necessity for human oversight. She emphasizes that while some positions may be at risk, particularly in application development, others will evolve rather than disappear. As CIOs navigate these transitions, clear communication and employee support will be paramount. Best practices include transparent discussions about potential layoffs, efforts to redeploy affected staff, and ongoing engagement to alleviate anxiety during organizational changes.
And from Windows On Theory, an analysis that highlights advancements in artificial intelligence (AI) could lead to significant economic growth, potentially doubling GDP within a decade. According to a report from Epoch AI, the training compute for AI models has been doubling every six months, suggesting rapid progress in capabilities. The article cites a study estimating that AI’s “doubling time” may accelerate even further, with predictions of substantial contributions to productivity across various sectors, particularly in software engineering. However, it is crucial to note that the impact of AI on employment remains uncertain, and while AI could replace certain jobs, it may also enhance productivity, ultimately reshaping the economic landscape.
Why do we care?
Questions to consider.
Are MSPs and IT service firms tracking anything resembling trust with clients—response time? satisfaction? renewal rate?
What would happen if trust were treated as a measurable KPI, not a soft concept?
And when trust erodes—how would you know before it hits revenue?
Which parts of your service delivery model are automatable, and which require irreplaceable human oversight?
Are leaders being transparent about what AI adoption really means for headcount, or hiding behind buzzwords like “efficiency”?
How can MSPs help clients navigate these same questions before fear undermines adoption?
If AI could double GDP within a decade, as some economists claim—what does that mean for service providers?
Are we ready for that level of acceleration, or are we still trying to stabilize billing automation and ticket triage?
Will productivity gains flow evenly, or mostly to hyperscalers and the enterprises controlling compute and models?
Can AI-driven organizations maintain human trust among staff, customers, and partners when automation starts deciding outcomes?