How to Work with Your AI: What to Consider Before Adding AI to Your Toolset
by Naomi Lariviere, CPO, Product Management & HX, ADP
Artificial intelligence (AI) has some great use cases. But it works differently than we're used to and can do things we're not used to. That's why choosing AI tools requires a new approach that begins with rethinking both what's possible, what we want to happen, and how AI can help.
Too often, organizations focus on the latest AI capabilities before considering how the technology will fit into the work itself. Yet successful AI adoption depends on more than selecting the right tool. It requires reimagining processes, establishing governance, building workforce AI literacy, and creating trust in how AI is used. Before investing in new AI-enabled technologies, HR leaders should consider four foundations for long-term success.
Key takeaways
AI transformation requires rethinking workflows, not simply automating existing processes.
Strong AI governance helps organizations scale innovation while managing risk, accountability, and compliance.
AI literacy and workforce training are essential for successful adoption and long-term value creation.
Employee trust, transparency, and human oversight are critical when deploying AI in HR and workforce processes.
Organizations should evaluate business outcomes, governance, workforce readiness, and trust before investing in new AI tools
1. Reimagine workflows before investing in AI tools
Real transformation happens when we re-sequence work around value, not legacy routines. Will the change cause fewer errors, resolve issues faster and improve workflow? Take payroll for example. AI can detect and validate variances before the run, escalate only what matters, and learn from every cycle. The payoff is fewer manual fixes, faster resolution, and greater trust in accuracy.
The shift to AI is as dramatically different as moving from typesetting to word processing. Instead of boxes of tiny letters and punctuation that get arranged into text and inked onto paper that is physically delivered to someone, we can create written text with a multitude of devices, create unlimited copies, and deliver the text almost instantly. We can even modify things that have been published. But it happened in phases with manual typewriters, carbon paper, and many gallons of correction fluid.
It's not always easy to imagine what is possible. And much of what happens next won't last, like fax machines. But we can identify where we're doing the same things but expecting new and different results. One example where we have not reimagined the process yet is chatbots that add steps or workflows that mirror old approvals. Sometimes, they create even more work. They rarely improve outcomes.
Instead of adding new tools to the ways we already work, the breakthrough comes when we redesign workflows end-to-end, embedding AI where it enhances human judgment, not where it replaces it.
To reimagine process, we must back up and clarify what problem we're trying to solve and where the real value is, then explore what new approaches are possible with AI.
Learn more about how ADP can help deliver better outcomes in the AI era
2. Build AI governance before you scale AI adoption
Governance isn’t about control. It’s about confidence. We want AI tools that are worthy of our trust. Good AI governance doesn’t slow innovation; it makes it sustainable.
When we introduce new tools that work differently, we also need a strong, well-thought-out AI governance framework to ensure that the tools are used by the right people for the right applications and are monitored for the right outcomes.
Too often, we rush to deploy, then scramble to build guardrails. Gartner predicts that over 40% of agentic AI projects will be canceled by the end of 2027 due to inadequate governance (“risk controls”), escalating costs and unclear business value.
For HR, this means going beyond bias audits. It’s about assigning ownership for every AI decision, aligning policies across teams, and keeping open conversations with employees about what AI is doing and why.
3. AI literacy and workplace training drive successful adoption
One of the top challenges HR faces when adopting software with AI features is having people who know how to work with it. A 2025 Capterra survey of employers found that 45% said that training or upskilling current employees was one of their top challenges. "However, only 39% of HR leaders consider training resources critical when researching software, even when the majority foresee an increase in costs in this field and are aware that they have to upskill their employees."
In addition, AI literacy gaps can be magnified when some functions adopt AI rapidly while others lag. At the same time, some employees regularly use LLMs on their phones and personal computers with varying levels of understanding of how they work, where they are most reliable, and how to check the accuracy of their output.
AI literacy will also develop differently for an organization with 8 employees than one with 80 or 800. While it makes sense to start with a small group or with a specific use case, eventually everyone should be familiar with how to interact with AI tools and how to monitor and assess their outputs.
As HR leaders we can drive the effectiveness of AI by:
Offering literacy pathways not just to technical teams but to operations, service, implementation/onboarding, and frontline roles.
Framing AI literacy as a career enabler, not a niche skill.
Tracking literacy metrics alongside adoption and value metrics.
When we level the field, we make AI adoption inclusive, fair, and effective. This is what “human” means in a connected future: everyone empowered, everyone competent.
4. Building employee trust in AI-powered work
Scale matters, but without trust, scaling AI becomes fragile.
For HR, that means the work is not just about moving fast, it’s about moving right by embedding transparency, dialogue, and accountability in the introduction and use of AI. This means informing employees about what data is used and why, how the tools work, and how to consider both the benefits and the risks of using them.
Trust also requires establishing human-in-the-loop checkpoints for use cases where there are matters at stake that affect people in significant ways. For HR, that's most of what we do.
When HR frames AI with purpose, the conversation shifts from “We built it” to “We built it together with trust, clarity, and human intent.” That is what being human means in the AI era.
How to prepare your organization for AI success
In short, before you buy new tools that use AI, start by reimaging the work itself. What can be eliminated or changed or combined with other things? What's missing? What else would be affected if you changed the process?
Then think through the risks and governance needed so the tools deliver the most reliable value. Build in the guardrails before you start.
Make sure the people using the tools understand how they work and how to use them safely and effectively. And know that eventually nearly everyone will encounter tools that use AI in their work, so start now to make sure the learning and competence is ahead of the need.
Last, confidence and trust are the key to the successful addition of any tool. They're even more important when using AI.
Learn how ADP can help organizations manage workforce complexity, maintain compliance and deliver better outcomes in the AI era
Other articles in this series:
How to Work with Your AI: What AI Is and What It Does
How To Work With Your AI: How To Ask AI Questions and Make Sense of What You Get
FAQs about implementing AI at work
What should organizations consider before adopting AI tools?
Organizations should evaluate workflows, governance requirements, workforce readiness, data practices, and trust considerations before implementing AI-enabled technologies.
Why is AI governance important?
AI governance helps organizations manage risk, improve accountability, support compliance efforts, and ensure responsible use of AI systems.
What is AI literacy?
AI literacy refers to employees' ability to understand, use, evaluate, and safely interact with AI-powered tools.
How can HR teams build trust in AI?
HR leaders can build trust through transparency, communication, human oversight, training, and clear governance policies.
Should AI replace human decision-making?
Most HR and workforce applications benefit from AI-supported decision-making combined with human review and accountability.
