In this two-part series on generative artificial intelligence (AI), Victory Strategies Director, Shawn Campbell, takes a look at the five “Ps” that organizations need to consider to successfully implement the use of AI into their workflows.

In Part 1 of this series, we explored the first two of five factors — what I call the five "Ps" — that every organization must consider when implementing AI: Purpose and People. We examined why a human-first approach is essential, and why investing in people's capacity to work alongside AI is just as important as the technology itself. In this second and final installment, we turn to the remaining three: Policy, Process, and Platform.

Policy: Governance Is Not Optional

AI governance provides an excellent framework for the necessary components of a comprehensive oversight strategy. Encouragingly, research suggests that roughly two-thirds of organizational boards are taking time to deliberately discuss AI – and that is a meaningful step in the right direction.

That said, a common disconnect remains: boards or CEOs directing their organizations to “do something with AI, and now!” without taking the time to deeply discern which AI tools to utilize and against which strategic objectives. Urgency without direction is a liability.

Equally important is integrity of the data that powers AI. Clean, current and trustworthy data is not a nice-to-have – it is a fundamental prerequisite. AI works best at enormous data scale and if the underlying data is corrupted or outdated, the outcomes can be far worse than doing nothing at all. This is one more reason to ensure a human remains in every decision loop.

Decision rights must also evolve to keep pace with the tools being used – clarifying who holds what authorities, well beyond decision-making. Leaders should be prepared for hallucinations, the term used for when AI generates incorrect, misleading or fabricated outputs. Therefore, any AI-generated content must be reviewed before it is acted upon or shared. Additionally, organizations should be thoughtful about the AI personas they deploy, ensuring that they align with the organization’s values, culture and professional standards.

From an organizational perspective and my experience as an HR executive, AI strategy should not rest solely with the CIO or CTO. HR, in particular, has a vital role to play in policy discussions given that AI directly affects how people work, how roles are defined and performance is measured. The broader executive team must be aligned, collaborative and actively engaged in shaping AI governance together – at the end of the day, it is a cross-functional responsibility.

Process: Evolve How You Operate

Much of the current conversation in this space centers on agentic AI – AI agents that act, decide and execute with increasing autonomy – and what leaders should be doing and thinking about in response. While we touched on the need for updating skills across the team (and especially ourselves!) in Part 1, we did not address the equally important need to update the operating model to unlock its fullest potential.

That does not mean the technology alone drives an updated operating model. Rather, we must understand how things must evolve to harness the technology effectively and how the human-to-machine, human-to-human, and machine-to-machine exchanges will drive operations differently. It is worth noting that operating model and organizational design are not synonymous. The former must evolve to meet change; the latter does not automatically follow. Form needs to follow function. We do not update the organizational charts simply because how we operate is changing – especially if we have not done the due diligence to understand how roles and responsibilities are shifting, and how that drives the way individuals and teams perform their work.

Workflows must ensure that both the machine and the team member are accounted for. We have moved beyond separating Information Technology, Operational Technology, and Artificial Intelligence into silos – it has all become decision infrastructure. Leadership thinking must evolve to address how we build trust in using the tools, how to best educate and empower our teams, how decision rights must keep pace with tool usage, and how we measure success – including the shift from traditional KPIs to KPAIs (Key Performance AI Indicators), a meaningful evolution in how performance is tracked in an AI-integrated environment.

Organizational strategy must thread all these areas together into a simple, coherent fabric that everyone understands and can act on. Above all, the goal is to use available technologies to enable faster, richer, and better decision-making that is connected to the organization’s strategic objectives through a deliberately designed, and agreed to, process.

Platform: Choose Tools That Serve Your Strategy

Having, owning or using great tools that are not applicable to the work we are doing is a waste of resources. AI is not worth the chase just “to simply have it.” The approach is to incorporate the right tools to enhance the strategic outcomes and advance objectives. AI is not truly ubiquitous – nor should it be. It need not be used for everything and in some cases, the AI tool can and will perform worse than the human doing the job today.

The effectiveness of AI ranges from extremely capable to nothing short of genuinely frustrating. I challenge every organization to ensure that a human remains in the loop, rather than launching “hyped up” AI tools into the organizational ecosystem and walking away. There are thousands of companies selling AI solutions today, but leaders must remember to do their homework: pressure test, seek out real-use cases, ask the hard questions, and bring healthy skepticism to the table.

Call to Action

AI is not a panacea – at least not yet. But the opportunity it presents is real, and the time to engage with it thoughtfully is now. The question is not whether AI belongs in your organization. The question is whether your organization is ready to lead with it — wisely, intentionally, and with your people at the center.

As you reflect on where your organization stands today, consider these actionable next steps:

Start with Purpose: Before adopting any AI tool, clearly define the organizational objective it is meant to serve. If you cannot articulate the "why," the investment is premature.
Invest in your People: Develop deliberate upskilling and reskilling programs. Build confidence, not fear, around AI – and reinforce the distinctly human skills no algorithm can replace.
Establish Policy: Ensure governance structures are in place, data is clean and current, and a human remains in every critical decision loop.
Evolve your Process: Revisit your operating model with fresh eyes. Understand how human-to-machine and machine-to-machine exchanges are reshaping how work gets done – and design workflows accordingly.
Be disciplined about Platform: Choose tools that serve your strategy, not the other way around. Pressure test, ask hard questions, and maintain healthy skepticism.

Above all, be open and honest with your teams as you explore and implement AI. Lean into the good, the challenging, and the opportune. Be present and available. Curate curiosity. The human in the loop is not an obstacle to AI – it is the very thing that makes AI valuable.

Authored By: Shawn Campbell, Director

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