Autotask Community Live 2026 opened with a clear message for MSPs and IT teams: AI is changing IT operations, but effective adoption depends on having the right operational foundation in place.
Connected systems, structured data, standardized documentation and consistent processes are what allow automation and AI to deliver real value.
Held ahead of Kaseya Connect 2026, the event focused on reducing operational friction, improving visibility and building scalable IT operations.
This recap highlights the key themes and takeaways from each session.
The real barrier isn’t tools — it’s fragmentation
State of IT operations: Kevin Sequeira
Kevin Sequeira opened the day by addressing a challenge many IT leaders recognize. Teams aren’t struggling because they lack tools — they’re struggling because their tools don’t talk to each other.
That fragmentation creates constant inefficiencies. Technicians spend time switching between systems and manually cross-referencing information instead of solving problems. During critical incidents, those delays quickly compound.
Kevin’s message was clear: a PSA can no longer function as a simple system of record. It needs to become a unified data layer that connects people, processes and systems into a single source of truth that supports automation and AI.
From features to connected workflows
IT operations product update: Alex D’Aquila and Thomas Griffith
Alex D’Aquila and Thomas Griffith shared how the IT Operations Suite is evolving to reduce friction and connect workflows across service delivery.
A key highlight was Digital Specialist for Ticket Triage, powered by Kaseya Intelligence, which improves ticket classification, routing and resolution speed. Beyond individual features, the focus was on creating a more connected system where data flows seamlessly across PSA, documentation and reporting to enable more efficient, scalable operations.
Top 10 operational dashboards and reports every IT leader needs
Dashboard deep dive: Natalie Mayo and Nicole LaFreniere
In this session, Natalie Mayo and Nicole LaFraniere emphasized that data (KPIs) alone does not create visibility. Teams need dashboards that surface actionable insights in time to respond.
The session encouraged teams to move beyond lagging metrics and focus on leading indicators such as SLA health, utilization and first call resolution that reveal operational issues early. The four key focus areas were:
- Profitability: Which clients are truly profitable, and which are quietly consuming more resources than they generate?
- Service delivery: Are SLAs being met consistently, and where are tickets stalling?
- Efficiency: How are technician hours actually being spent, and where are the bottlenecks?
- Quality: How often are issues resolved during the first interaction, and how often are they escalating unnecessarily?
The goal isn’t to track more data but to track the right data in real time, so teams can respond rather than react.
Customer insight: Kobe Dudley
Customer speaker Kobe Dudley, Director of Managed Services at BECA, summed up the KPI discussion with a simple point:
“Not all revenue is good revenue.”
Dashboards helped his team identify clients consuming excessive technician time, improve staffing decisions and catch operational issues earlier. He also noted that visible metrics improve accountability and technician performance.
Building a repeatable IT assessment and roadmap engine
Technical deep dive: Elise Rodriguez and Sofiia Alieinik
Elise Rodriguez and Sofiia Alieinik introduced a structured approach to turning assessments into a scalable, repeatable process.
Instead of one-time reports, they outlined an assessment engine built on client segmentation, standardized frameworks and consistent cadence, designed to drive continuous progress.
Customer insight: Matthew Brouillard
Matthew Brouillard reinforced the session’s message with a simple reminder:
“Don’t try to cover everything. Focus on the three to five things that matter most to the client.”
His team built a three-step framework that any team member can execute:
- Standardize the process: A structured, repeatable framework creates consistency, reduces prep time and turns assessments into something your whole team can confidently execute, not just your top performers.
- Curate instead of covering everything: Tailored question sets based on client type keep conversations relevant and prevent assessments from becoming generic box-checking exercises.
- Organize for usability: Tagging and categorization turn static documents into a system that works in practice. It ensures consistency, helps junior team members know what to include and allows you to quickly pull the right questions for different scenarios.
AI outcomes start with structure, not hype
Technical deep dive: Jose Anthony Quintero and Alonzo Zepeda
Jose Anthony Quintero and Alonzo Zepeda reinforced a critical message: AI is only as effective as the structure behind it.
Clean data, consistent processes and structured documentation are essential for AI to deliver value. Without that foundation, AI amplifies inefficiencies instead of solving them. The takeaway was clear: organizations that invest in data maturity today will be best positioned to unlock meaningful AI outcomes.
What AI readiness looks like in practice
Customer fireside chat: Chris Swecker and Jason Laporte
The final fireside session brought two customers onto the stage to talk candidly about what becoming AI-ready looked like inside their organizations. Both faced the same challenge. Growth had created operational chaos. The solution was structure.
- Chris Swecker from Appalachia Technologies explained how his team tackled inconsistency by using their best-documented client environments as benchmarks. “We took a couple of clients we do really well and made them the gold standard. This is how we want documentation to look; this is the level of detail we expect,” he shared. Standardizing documentation improved onboarding made institutional knowledge accessible and reduced dependence on individual expertise.
- Jason Laporte, from Power Consulting Group, described a similar turning point inside his organization. “Our growth was inhibited by our inability to scale. Once we standardized how we document and store information, we removed those bottlenecks.”
Both speakers emphasized the same point. Early growth often depends on tribal knowledge held by a few key people, but that model does not scale. Capturing knowledge in structured, accessible systems creates resilience, enables teams to work more independently and supports long-term growth.
The foundation is the strategy
By the end of the event, one idea surfaced repeatedly in every session: the foundation matters more than the tools built on top of it.
Sophisticated AI features don’t overcome fragmented data. A powerful reporting dashboard doesn’t help if teams don’t know what to do with the numbers. A capable platform can’t compensate for inconsistent processes. The teams seeing real results — from AI, from automation, from better client relationships — had done the work first. Clean data, standardized processes and build documentation worth trusting.
That’s the foundation. Everything else gets built on top of it.
That’s the shift Autotask Community Live 2026 was pointing toward, and it’s one worth taking seriously.
For more product updates, operational strategies and technical insights, watch our upcoming webinar sessions.
