To Earn Trust For AI Rollouts, Follow The Order Of Operations

Robbie Morrison, CEO of Velosio, is a technology leader with 30+ years of experience driving business success through innovative solutions.

​The AI imperative is here, and for many organizations, it arrived more than a year ago. Yet the pressure to adopt AI that delivers real business results keeps rising, even as 70% of those tasked with verifying AI outputs only sometimes, rarely or never check the answers.

No wonder the debate around AI and business trust keeps moving. A defined AI order of operations can help build the element every technology rollout depends on: trust.

Clean Data Foundation Always First

Your people will not fully trust the AI systems and layers you ask them to use if those systems begin with poor data. The data behind your business AI layer directly shapes the reliability of the outputs users get back. Companies that skip the data cleanse may see short-term movement, but a long-term AI launch requires data architecture evaluation as step one. ​

Governance And Security

A very close second step, so close it may need to move in tandem with your clean data foundation, is governance and security. Data management your team can depend on helps ensure that your AI model only returns information users should have access to. Otherwise, you risk exposure that weakens credibility inside and outside the organization. Control access and permissions before data gets near the AI model. ​

Onboard Agents With Guardrails

The third step in AI’s order of operations is onboarding each agent as if it were a new employee. Give it guardrails, defined swim lanes, goals and permissions where they are needed. Not every agent needs the same onboarding path. We’ve seen clients, particularly in professional services, make progress when they embed AI with purpose-driven tasks in mind. Just as with employees, the role matters. Consider what each agent is designed to do and set it up with only what it needs to do that job. ​