In several recent projects, we have been working with remote contractors who are actively building or supporting AI-related solutions. Because AI delivery cycles move quickly and capabilities evolve through experimentation and iteration, not everything is fully rolled out or stabilized at the time work is underway.
This sometimes leads to contractors asking for clarity or certainty on workflows, tools, or next steps that are still changing.
How do you respond to these questions in a way that maintains trust and momentum, without over-committing or creating confusion when parts of the AI solution are still in flux? What communication practices have you found effective in AI-driven projects where change is the norm rather than the exception?
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Sergio Luis ConteHelping to create solutions for everyone| Worldwide based OrganizationsBuenos Aires, Argentina
AI is a board term. For example, if you are implementing AI components inside a solution related to manufacturing automation it is totally different than if you are implementing AI to automate repetitive tasks that belongs to flow of office process. When you clearly define the context and the type of AI entities you need to use and implement then you can select the life cycle and how you will interact with all stakeholders to create the solution. Nothing new below the sun. Saving Changes...
Project Manager| AWR Development (BD) Ltd. Cox's Bazer , Bangladesh
Hi Bruce, What’s helped me most is being very open about what’s stable and what’s still evolving. Clear short-term priorities, frequent check-ins, and shared visibility into changes help contractors stay confident even when the bigger picture is still taking shape.
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Armando HerreraProject Manager| ONEJOON INCRoswell, Ga, United States
Hi Bruce,
AI is a broad term, and the approach depends heavily on context, for example, implementing AI components in manufacturing automation is very different from automating repetitive office workflows. When contractors seek clarity in areas still evolving, I focus on transparency and adaptability: clearly state what’s stable and what’s still under review, document and communicate changes promptly, and create short feedback loops to maintain alignment and trust. Using living documents, decision gates, and regular updates helps prevent confusion while keeping momentum. That said, fully answering this question requires deeper detail on the specific AI domain and project scope, as best practices vary significantly across use cases. For PMI professionals, the key is to apply core project management principles (structured communication, stakeholder engagement, and iterative planning) while embracing the flexibility that AI innovation demands.
Program Manager| HARPER SRLSanto Domingo / Distrito Nacional, Dominican Republic
In fast-moving AI projects, I’ve found trust comes from clarity about uncertainty. I’m explicit with contractors about what is stable today, what is still being explored, and what decisions are time-boxed rather than final. Short planning horizons, frequent touchpoints, and visible change logs help avoid false certainty while keeping momentum. When expectations are framed around learning cycles instead of fixed answers, collaboration stays productive even as the solution evolves. Saving Changes...
Omar JabbarProject Management and Digital Transformation Consultant| OGreen IT Service Inc.Ontario, Canada
Always prioritize simplicity in management. Foster open communication by regularly inviting contractors to share insights and ask questions, which helps team members feel supported and connected. Encourage collaboration and adaptability throughout the project. I utilize Microsoft Teams Channels for each stream and have added all project team members to these channels so they can seek clarification or raise any issues. Additionally, all status and progress updates are posted there weekly to ensure everyone is on the same page. Saving Changes...
The use of evolving technologies helps stimulate communication in AI-driven projects. Saving Changes...
Luis BrancoCEO| Business Insight, Consultores de Gestão, LdªCarcavelos, Lisboa, Portugal
In fast-moving AI projects, clarity does not come from fixed answers but from disciplined transparency.
What has worked well for me is being explicit about what is stable versus what is still exploratory. Saying “this is the current direction, and it may evolve” builds more trust than pretending certainty where it does not exist.
Second, I avoid long-range commitments and instead align on short, time-boxed objectives. Clear goals for the next iteration create momentum without accumulating expectation debt.
Third, adaptation needs to be part of the psychological contract from the start. In AI work, change is not a failure of planning, it is the operating condition. Contractors should know how decisions evolve, who decides, and based on which criteria.
Finally, explaining the why behind changes matters as much as explaining the what. When people understand the rationale, uncertainty feels intentional rather than chaotic.
In AI projects, trust is sustained less by predictability and more by clear governance, transparent decisions, and continuous learning. When those are present, change stops being noise and becomes part of the system. Saving Changes...
Tim McClungProject Coordinator| New Hanover County ITWilmington, Nc, United States
In fast-moving AI projects, I’m upfront about what’s been decided, what's being tested, and what's still unknown. I’ve found that clarity about uncertainty builds more trust than false certainty.
I focus conversations with contractors on short, outcome-based goals, frequent check-ins, and clearly defined decision points. This keeps momentum without over-committing, while giving everyone confidence that changes are intentional, not chaotic. Saving Changes...
Senior IS Project Manager| Baycare Health SystemsClearwater, Fl, United States
Hi Bruce - not all fast moving projects are AI projects, so I would implement the same techniques for your AI projects as you would use for any fast moving project. Communications with stakeholders and other team members is critical to ensure that the real customer requirements are satisfied. Are you managing this work using Agile methodology? Stand-up calls with key stakeholder involved are a great way to get the developers quested answered in a timely manner. Saving Changes...
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