General tools, general results

AI tools like ChatGPT and Gemini are force multipliers for individual productivity when put in the right hands. But despite the promise of large language models, they’re falling short of delivering transformation-scale outcomes for large and matrixed enterprise revenue teams.

Fundamentally, enterprise software succeeds when it drives systemic behavior change. Salesforce is a $250B company because its products are purpose-built to help executives drive org-wide GTM transformation and deliver real enterprise value. Large language models (LLMs) alone, while useful products, won’t deliver transformation for the scaled revenue teams that need it most.

Here’s why:

LLMs weren’t designed for sales

LLM tools are general-purpose products, built for anyone and everyone. Students writing book reports, couples planning a vacation, financial analysts running due diligence–everyone needs to find something useful for a product like ChatGPT to succeed.

Despite training on massive datasets, LLMs aren’t built around the specific context, methodologies, and domain expertise of revenue leaders. They don’t understand your specific GTM motions, sales playbooks, competitive landscapes, or buyer personas. They lack the industry-specific knowledge and know-how that differentiates your top performers from average sellers.

Sales success requires a deep understanding of customer challenges, along with how you uniquely solve them, all distilled into precision messaging aligned with specific buying processes. General LLMs can help craft emails or summarize calls, but they can't replicate the strategic frameworks developed by sales leadership or encode your company's unique value propositions to give your sellers an edge in the market.

Scale matters

Driving transformational change in the largest organizations is fundamentally about process, not just individual productivity. Without imposing process around AI tooling, you're left with inconsistent execution across sellers and fragmented knowledge across the organization.

The core challenge is structural. General-purpose LLMs lack the connective tissue that enterprise transformation requires:

• No standardized workflows: Each seller creates their own prompts, develops their own methodologies, and establishes their own best practices. This creates massive variance in output quality and approach across teams, leading to an inconsistent customer experience and sales results.
• Absent governance: There's no central oversight of how AI tools are being used, what information is being shared with them, or whether outputs align with company value frameworks, positioning, and messaging.
• Isolated impact: There's no mechanism to capture, validate, and distribute insights across the organization. Reps can wring useful information out of ChatGPT, but you can’t scale the impact of those insights when they sit in a single person’s browser window. Even more so, when territories change or there’s turnover, account intelligence gets lost in the shuffle.

True enterprise transformation requires AI explicitly designed for collaborative selling environments—solutions purpose-built to standardize processes, capture institutional knowledge, and distribute intelligence org-wide.

Models aren’t real-time

LLMs alone are detached from current reality. Yes, ChatGPT and other tools can search the web. But LLMs with web search look more like content regurgitation than valuable enterprise software. Value for revenue orgs won’t come from finding the most search-optimized webpage, it comes from building a complete picture of the customer across all available data points.

Think of all the changes that happen in a market or company within a week, let alone a year–new products, acquisitions, leadership changes, macroeconomic changes. How do they all connect, and how should that inform an account team’s approach to the opportunity? Understanding those critical events is the basis for an intelligent point of view on your customer’s business. Without that comprehensive view, account teams sound the same as everyone else using ChatGPT.

Winning POVs for enterprise sales, delivered at scale

We talk to a lot of revenue leaders, and AI is front of mind for nearly all of them. The current landscape offers more questions than answers, but forward-thinking companies like Dialpad are choosing Poggio as the cornerstone of their AI strategy. They’re arming account teams with winning points of view to close bigger deals faster and are achieving real enterprise value today.

Here’s why:

• Built for sales: Poggio is built exclusively for revenue teams. Poggio is configurable to match your specific GTM motion, with account intelligence focused on bringing an executive-level POV to every conversation.
• Delivered at scale: A single, exec-level point of view is a nice to have. High-quality POVs across your entire account universe, available for everyone that touches the account to access and collaborate from? That’s transformational.
• Always current: Poggio’s AI agents are constantly scanning thousands of data sources for relevant, exec-level insights. This intel automatically updates each account POV, arming account teams with 24/7 intelligence available on demand so they stand out as a strategic partner in every conversation.

Visit poggio.io to learn more.