Exec Roundtable on 2026 Planning

Your 2026 budget meetings aren't about doing more with less anymore. They're about doing different with better. In a recent HubSpot roundtable, three leaders managing everything from 71 golf clubs to global SaaS operations revealed a truth: the companies winning in 2026 aren't the ones with the most AI pilots. They're the ones who finally connected their data.

38% of organizations are actively piloting AI initiatives, with another 24% already scaling implementations. Yet the gap between experimentation and transformation remains wide. The difference? Leaders who treated data unification as the non-negotiable foundation, got specific about workflows instead of throwing AI at broad problems, and measured business impact instead of adoption vanity metrics.

The path forward isn't waiting for perfect clarity. It's building the infrastructure that works regardless of which AI capabilities emerge next.

The Data Foundation Imperative

Patrick Damer, VP of RevOps at Arcis Golf, faced a problem that likely sounds familiar to most operations leaders. Arcis Golf was drowning in platforms (120 of them). Every department had dashboards. Every dashboard told a different story. And leadership couldn't get a straight answer about what was actually happening across their 71 golf and country clubs across 14 states.

Rich in data, poor in connection

This year, Arcis Golf consolidated their tech systems with a goal to create alignment across all departments with a single source of truth. By eliminating friction, real insights finally surfaced and drove measurable results across the entire organization.

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The "bolt on another platform" approach feels productive in the moment. There's a problem, you add a solution. But the hidden cost compounds quickly. At Arcis Golf, this meant 21 million point-of-sale transactions every month that couldn't talk to CRM data, which couldn't talk to sales activity, which couldn't inform marketing decisions.

According to Google's 2025 ROI of AI Report, 41% of organizations are prioritizing data quality enhancement as their top investment to accelerate AI adoption. That's not because data quality is trendy. It's because leaders realized you can't build AI on a shaky foundation.

Unified data isn't a marketing term. It's the difference between spending three days pulling together an answer and getting that answer conversationally in three minutes. Chris Hogan, SVP of Operations & Strategy at HubSpot, described HubSpot's internal vision: conversational analytics where any team member can ask their system a question like "Why did small business close rates decline in October?" and get back insights from call transcripts, deal data, and product usage in one response.

That's only possible when your business logic is centralized, when data sources can flow in without friction, and when structured data (your CRM records) connects seamlessly with unstructured data (your emails, calls, and documents). AI unlocks what's trapped in that unstructured layer, where 80% of customer intelligence typically lives unused.

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The maturity curve matters. HubSpot has data engineering teams. Most mid-market companies don't. Chris's advice: understand where you are on that curve and don't try to copy companies operating at a different level. Look for vendors who can help you accelerate rather than building everything in-house.

Patrick's team took a different path forward by consolidating onto platforms that could handle their specific workflows. The goal wasn't perfection. It was removing friction so insights could actually happen.

🕵️Looking for a Data Agent? Breeze data agent researches and answers custom questions about your customers using your CRM, calls, emails, documents, and the web. Learn more.

AI: From Pilots to Production

Why Most AI Pilots Fail

HubSpot spent early efforts trying to "AI-enable the sales team." That's too broad. It led to throwing tools at walls and watching nothing stick. The breakthrough came when they got specific: exact persona, exact workflow, exact problem.

For example, HubSpot sales reps were spending 30% of their time on account qualification when they first received an account. Same repetitive process, different accounts, all day long. They attacked that specific workflow with AI, replicating the exact steps reps used to take through automated prompts and analysis. The result: massive time savings that reps could redirect to actual customer conversations.

Rocket ship

HubSpot started tracking weekly active AI usage. Reasonable metric, right? Except it didn't correlate with business results. They shifted to measuring AI-assisted deals: what percentage of significant opportunities actually used the guided selling tools? That's what moved close rates and deal velocity.

According to Google's 2025 ROI of AI Report, 28% of organizations struggle with measuring AI impact. The fix: stop measuring adoption and start measuring business outcomes.

Time freed up for customer interactions.
Close rate improvements on AI-assisted versus non-assisted deals.
Speed to insight on critical decisions.

Blueprint

Patrick's approach at Arcis Golf: focus on automation and customer intelligence. Not replacing humans, but augmenting the 80% of work AI can handle so teams focus on the 20% that unlocks real growth. He calls it shifting from "doing the work" to "designing systems that do the work."

Start small. Prove value. Scale what works. And critically, invest in the people side: training, process optimization, building confidence in AI throughout the organization.

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Chris noted that last year's budget cycles looked different. AI was newer, less mature, and teams didn't allocate significant resources for agent adoption or unstructured data projects. This year's planning is fundamentally different. Organizations are setting aside real budget for experimentation and scale.

The 2026 Mantra: Fewer Bets, Bigger Impact

Arcis Golf's strategy comes down to a principle their founder champions: fewer bets, bigger bets. Rather than spreading resources thin trying to do everything, they're doubling down on what moves the needle: automation and customer intelligence. Their investments focus on the people side: training, process optimization, and building confidence in AI and automation across the organization.

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Loop Marketing Methodology

Karen mentioned HubSpot's internal teams use Loop Marketing to align brand, content, and revenue operations. It's the framework connecting human creativity with AI amplification, helping teams shift from SEO to AEO (AI Engine Optimization) and diversify beyond traditional channels.

Explore Loop Marketing

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See Breeze Agents in Action

Patrick said Acris Golf is evaluating customer agents for 2026 while Chris described conversational analytics capabilities HubSpot teams leverage internally. Breeze Agents brings this vision to your CRM with pre-built solutions and the ability to build custom agents for your specific workflows.

Discover Breeze

Sales rep

Talk to a Planning Expert

Planning for 2026 means making strategic decisions on data infrastructure, AI investment, and team alignment. Our team works with hundreds of companies navigating similar challenges and can share what's working for organizations like yours. Connect with a rep to explore HubSpot's unified platform.

Frequently Asked Questions

The roundtable featured three leaders discussing how to approach 2026 planning differently. Key topics included data unification as a foundation for AI success, identifying specific workflows for AI implementation rather than broad experimentation, and measuring business impact instead of adoption metrics.

Data unification enables AI to work effectively by connecting structured CRM data with unstructured sources like emails, calls, and documents. Without unified data, organizations struggle to extract insights. Arcis Golf consolidated 21 million monthly point-of-sale transactions with their CRM data to create a single source of truth, enabling real insights and measurable results.

Instead of tracking vanity metrics like weekly active AI usage, focus on business outcomes. HubSpot shifted to measuring AI-assisted deals and the percentage of significant opportunities using guided selling tools, which directly correlated with improved close rates and deal velocity.

Loop Marketing is HubSpot's framework that aligns brand, content, and revenue operations. It connects human creativity with AI amplification and helps teams transition from traditional SEO to AEO (AI Engine Optimization) while diversifying beyond conventional marketing channels.

Breeze Agents are HubSpot's AI-powered solutions that can be pre-built or customized for specific workflows. They include capabilities like the Breeze data agent, which researches and answers questions about customers using CRM data, calls, emails, documents, and web sources.