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Who’s best suited to drive A.I. adoption in organizations: business leaders, HR, or external consultants?

Writer's picture: Shveta MalhanShveta Malhan

Updated: Nov 1, 2024




I’ve been thinking about this a lot, especially after reading the recent report by the Vector Institute and the Conference Board of Canada. Plus, drawing from my own experiences across business (Intel, GE), consulting (Deloitte), and HR at Canadian companies, I’ve come to a realization: A.I. adoption isn’t just about bringing in new tech. It’s about cultural change, shifting mindsets, upskilling, and—above all—building trust.


But let’s be real: with both business and HR stretched thin, who’s really in the best position to drive this change?


🌟 Business teams have their hands full with operational goals. They’re often knee-deep in frameworks like Six Sigma and Lean to streamline processes and solve problems—I’ve used these tools myself, and they’re incredibly powerful. But here’s the thing: as the report points out, Canada’s A.I. adoption rate is only half that of the U.S. Many organizations simply don’t have the capacity for the kind of cross-functional, people-centered transformation that A.I. truly requires.


🤝 HR, on the other hand, has a unique opportunity to lead. But let’s be honest, HR also faces some serious challenges—like being stretched for time, lacking resources, and, sometimes, missing key capabilities. And then there’s the big one: trust. According to the report, a lot of employees are worried about what A.I. means for their jobs and ethical concerns. From my own experience, trust in HR can be shaky too—people often see HR as the “hiring and firing” department. That perception makes it tough for HR to lead a transformative change, especially when employees are unsure about how A.I. might affect their roles.


So, how can HR rise to the occasion and tackle these trust and adoption challenges head-on?


Here are some actionable steps HR can take to become a strategic enabler of A.I.:


1. Develop Data Literacy to Drive Insights:


  • For HR to effectively adopt and lead A.I. initiatives, data literacy is essential. This means building the ability to understand, analyze, and draw actionable insights from people data. By upskilling in data literacy, HR can leverage data-driven insights to make informed decisions about workforce trends, identify areas of potential employee readiness and resistance along with areas ready for A.I. implementation, and demonstrate the ROI of A.I. investments to leadership.

  • Building data literacy also empowers HR to engage actively with data scientists and technical teams, ensuring that A.I. solutions are effective and relevant to employee needs.


2. Upskill in Process Re-Engineering, Agile Change, Design Thinking:


To drive A.I. adoption effectively, HR can leverage multiple methodologies.


  • Process Re-Engineering Methodologies: Tools like Six Sigma and Lean can help HR build process re-engineering muscle. Leading process reengineering workshops (from the people lens) with the business will help HR map out workflows in detail and identify areas where employees are experiencing friction in their work flows. This will help business identify areas where employees could interact with A.I. in their daily work, ensuring a smoother integration. This also helps HR understand work dynamics deeply and communicate effectively with the business, making it a credible and impactful transformation partner, influencing people decisions. 

  • Agile Change Management: Focuses on adaptability, providing HR with tools for implementing iterative, responsive change strategies that match the rapid evolution of A.I.

  • Design Thinking: Emphasizes human-centered problem-solving, ensuring A.I. initiatives address real employee needs and enhance their experience.


By combining process engineering, agile, design thinking, HR can design A.I. adoption strategies that are flexible, empathetic, and deeply rooted in the organization's culture.


While external consultants will always play a role, HR can use these enhanced skills to become an informed partner—balancing internal expertise with external guidance to achieve sustainable outcomes.


3. Collaborate Rather Than Over-Rely on Consultants:


  • HR can work directly with business leaders to develop A.I. strategies that put people first. This reduces the need to overly depend on external consultants and helps build ownership within the company.

  • An effective collaboration might look like this: HR leads by defining cultural and people needs, while consultants provide the technical insights for A.I. implementation, ensuring tailored solutions that fit the company’s context and culture. Consultants still have an important role, but HR can lead these engagements to make sure the A.I. solutions are sustainable and fit well with the company culture.


The Opportunity for HR:


If HR can evolve beyond its traditional roles and embrace a combination of data literacy, process re-engineering, agile change management, and design thinking, it can lead the charge on A.I. adoption.


People insights will be their decision-enabler, process re-engineering will drive efficiencyagile change approaches will ensure adaptability, and design thinking will keep employee needs at the forefront of A.I. initiatives.


HR can be the bridge that helps companies move forward with A.I., acting as a strategic partner leading the people stream of transformation. By leveraging its enhanced capabilities, HR can ensure A.I. solutions are not only implemented effectively but also embraced throughout the organization.


Addressing trust—in both A.I. and in HR itself—will be key to making A.I. adoption successful for Canadian companies, keeping employees engaged and at the center of this transformation.


What do you think? Can HR step up and become the trusted leader in A.I. adoption, or will it always be a game for consultants?


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