Speed isn’t always a virtue. In high-volume hiring, rushing can do more harm than good - to candidate trust, recruiter efficiency, and the bottom line.

At inploi, we believe that AI should accelerate what matters, not just what’s easy to measure. That’s why we’re taking a different approach: one that blends intelligent automation with smart friction to build candidate trust, reduce operational waste, and improve hiring decisions over the long term.

The automation trap

Many TA teams are being pushed to move faster: shorter funnels, quicker decisions, fewer human touchpoints. But this pursuit of velocity often ignores a critical truth:

Speed alone doesn’t build trust. Relevance, clarity, and care do.

When AI is used purely to eliminate steps, rather than enhance experiences, candidates get confused, overlooked, or alienated. And TA teams miss the signals that actually drive better outcomes.

Think of:

• Bots that ghost candidates mid-process

• One-click applies that flood ATSs with irrelevant CVs

• Matching algorithms that discard high-potential talent based on rigid filters

These aren’t just technology issues. They’re trust issues. And in a competitive talent market, trust is what wins.

Slowing down to improve outcomes

We’re not against speed. But speed must be purposeful.

We think about intentional friction as a strategic design principle - a way to slow down where it matters, not to delay, but to enhance decision quality and build trust. That means rethinking how journeys are structured, how AI is deployed, and where moments of clarity and care can create stronger outcomes.

Here’s how that thinking shows up in practice:

Candidate-guided journeys

Instead of pushing people through rigid funnels, consider giving candidates more agency. When job seekers can explore roles by job family, ask questions through a chatbot, or choose their preferred next step, engagement improves. It’s about meeting people where they are, not where the process assumes they’ll go.

Wildcard suggestions

Matching algorithms tend to be overly narrow. But subtle interventions, like suggesting adjacent roles that align with a candidate’s broader skill set, can surface potential that might otherwise be missed. This helps candidates discover new paths, and helps employers uncover hidden talent.

Insight over automation

Not every drop-off is a problem, but some are. Having real-time visibility into candidate engagement, journey friction, and funnel performance allows hiring teams to respond intentionally, not reactively. It’s about using AI to guide human decisions, not replace them.

For example, one inploi client discovered that 40% of drop-offs occurred after job description views. With this insight, they tested clearer role summaries, and improved application conversion by 17%.

Why smart friction works

When we speak to Heads of Talent and HRDs, a recurring concern is this: “How do we move faster without losing the human touch?”

Our answer: Don’t eliminate friction. Design it.

Because the right kind of friction:

• Helps candidates make better decisions

• Surfaces fit that goes beyond CV keywords

• Reduces false positives and mis-hires

• Builds credibility with frontline talent

• Signals care, not indifference

As a result, companies get:

• Higher-quality applications

• Shorter time-to-productivity

• Improved candidate sentiment

• Lower drop-off rates

And all of that translates into measurable business impact, not just TA efficiency metrics.

The long game: Future-proofing with intentional AI

AI will continue to reshape hiring. But the winning TA strategies won’t be those that blindly automate. They’ll be the ones that use automation to deepen relevance, surface hidden insights, and improve human decision-making.

Candidate expectations are evolving. Trust, transparency, and clarity are becoming table stakes. In a noisy market, how you make candidates feel during the journey will often outweigh how fast you move them through it.

So before you strip another step from your process, ask:

• Are we solving for speed, or quality?

• Does this automation build trust, or break it?

• What insight are we missing by moving too fast?

If you’re evaluating AI in your hiring stack, don’t just ask what it automates. Ask what it reveals, what it improves, and how it builds trust.