Using agentic AI to transform B2B GTM, content, and pipeline generation

The evolution of agentic AI from innovative curiosity to mission-critical backbone of B2B go-to-market (GTM) strategies has reached a decisive inflection point in 2028. What began as experimental, siloed AI workflows has matured into fully integrated, multi-agent ecosystems that autonomously orchestrate revenue generation, pipeline acceleration, and customer engagement at scale. Recent developments—including high-profile acquisitions, market reactions from enterprise giants, deepening vertical specialization, and the emergence of robust governance frameworks—further cement agentic AI as the defining architecture of modern B2B GTM.

Building on the foundational shifts previously observed, this updated analysis synthesizes new market signals, technological breakthroughs, operational paradigms, and strategic insights shaping how B2B organizations must embed, govern, and operationalize agentic AI to thrive in an increasingly AI-native commercial landscape.

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Agentic AI: The Unquestioned Infrastructure Powering B2B GTM Excellence

Agentic AI platforms now function as indispensable infrastructure, autonomously managing complex, multi-agent workflows that span the entire revenue lifecycle—from prospecting to closing and post-sale engagement. Key transformative dynamics include:

• Multi-agent orchestration transcends the fragmented SaaS stacks of old, enabling real-time, dynamic buyer engagement and continuous account segmentation at previously unattainable velocity. This orchestration drives measurable improvements in deal velocity, pipeline conversion, and customer lifetime value.
• Embedded AI agents within core enterprise applications continue to proliferate. Atlassian’s Jira agents, for example, automate triage and cross-functional collaboration seamlessly, exemplifying how AI augments daily workflows rather than complicates them.
• Agent-to-agent commerce is rapidly gaining ground as AI agents autonomously negotiate contracts, manage procurement, and execute transactions across organizational boundaries—ushering in a frictionless, scalable B2B transaction paradigm.

Dan Lee, CEO of Nooks, encapsulates this shift:
"AI-native sales tools are not incremental upgrades; they fundamentally rewrite the GTM playbook."

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Market Consolidation and Disruption: Anthropic-Vercept and Salesforce’s Strategic Signals

The market is crystallizing around a smaller cadre of deeply capable AI platform providers driving the next wave of GTM innovation:

• Anthropic’s acquisition of Vercept represents a landmark consolidation in autonomous workflow orchestration. Vercept’s technology enhances Anthropic’s capacity to deliver enterprise-grade agentic AI with end-to-end governance and scalable task automation. This move signals a broader trend toward concentration among AI leaders who can provide robust, compliant, and reliable multi-agent platforms.
• The enterprise software sector reacted sharply to Salesforce’s recent $46 billion revenue guidance, which many interpret as a warning shot about the “agentic disruption” looming over legacy CRM and GTM models. AI-native competitors deploying autonomous, multi-agent orchestration solutions threaten to outpace traditional static workflow systems, forcing incumbents to accelerate AI integration or risk erosion of market share.
• These developments underscore the urgent imperative for incumbent GTM leaders to aggressively embed agentic AI or face displacement by more agile, AI-first challengers.

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Verticalized Agent Platforms: Building Deep Domain Moats Across Regulated and Complex Markets

Vertical specialization in agentic AI is now a strategic differentiator, with startups and platforms embedding domain expertise, compliance frameworks, and workflow automation to create defensible competitive moats:

• Basis’s $100 million raise at a $1.15 billion valuation exemplifies deep penetration of AI agents in accounting, tax, and audit workflows, sectors where regulatory compliance is paramount.
• Harper’s $47 million funding (seed plus Series A) demonstrates growing AI-native disruption in regulated commercial insurance brokerage workflows.
• Sherpas ($3.2 million) and Kinfolk ($7 million) have launched AI-driven advisory and HR operations agents, respectively, embedding verticalized intelligence and compliance into specialized enterprise functions.
• Marketing intelligence and adtech platforms such as Profound ($96 million Series C) and Koah ($20.5 million Series A) continue to push verticalized AI into nuanced B2B GTM roles.

These verticalized agents deeply embed critical compliance, regulatory guardrails, and domain workflows, raising switching costs, preventing commoditization, and driving sustained differentiation—especially crucial in heavily regulated domains like finance, insurance, and healthcare.

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Trust, Governance, and Production Controls: Essential Pillars for Safe Agentic AI at Enterprise Scale

As agentic AI scales beyond pilot programs, trust and governance frameworks have become non-negotiable to mitigate operational, regulatory, and reputational risks:

• Startups such as t54 Labs (backed by Ripple and Franklin Templeton) are pioneering “trust layers” that enforce governance, compliance, auditability, and real-time risk mitigation across distributed agent ecosystems. Their recent $5 million seed round accelerates innovation in production-grade controls.
• Anthropic has integrated governance copilots directly into agentic workflows, ensuring continuous compliance enforcement, operational reliability, and comprehensive audit trails.
• Notorious incidents like the “Claude Code” uncontrolled prototyping episode highlight the dangers of insufficient production controls, reinforcing the industry's focus on robust safety and reliability mechanisms.
• Enterprises, particularly in finance, healthcare, and legal sectors, now demand embedded compliance guarantees and SLA-backed contract frameworks to reduce risk and assure AI decision accuracy.

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Infrastructure Breakthroughs and Democratization: Enabling Scalable, Cost-Effective AI Deployments

Technological advancements underpinning agentic AI continue at a rapid pace, enabling low-latency, high-throughput, and cost-efficient deployments critical for real-time GTM workflows:

• The Intel–SambaNova $350 million partnership is driving inference-efficient AI hardware adoption, challenging legacy GPU models with scalable, cost-optimized solutions.
• The Taalas HC1 chip breaks new ground, delivering over 17,000 tokens per second on Llama 3.1 8B, a milestone that supports embedding AI agents in latency-sensitive sales and marketing processes.
• Real-time data ingestion and orchestration platforms like Nimble ($47 million Series B) and Union.ai ($19 million extension) maintain AI agent accuracy and relevance by ensuring fresh, compliant data flows.
• Cernel’s $4.7 million seed raise supports scaling autonomous contract execution, a critical enabler for agent-to-agent commerce ecosystems.
• Democratization efforts lower barriers for non-technical users to build and deploy AI agents at scale:
  • SolveAI’s $50 million Series A empowers citizen developers to create production-grade autonomous agents.
  • Guidde’s $50 million raise delivers embedded AI training and onboarding guides for rapid organizational adoption.
  • Letter AI’s Compass ($40 million Series B) integrates real-time AI deal guidance into revenue teams’ workflows, closing the loop between orchestration and sales outcomes.
• Tooling ecosystems increasingly bifurcate around leading vendor platforms:
  • Microsoft Copilot Studio focuses on rapid, low-code agent creation tightly integrated with Microsoft 365 and Azure.
  • Microsoft Foundry offers a more modular platform for complex, bespoke multi-agent orchestration favored by large enterprises.

Enterprises face critical choices between these platforms based on scale, customization needs, and ecosystem fit.

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Operational and Organizational Transformations: Engineering-Driven GTM and Novel Monetization Models

The operationalization of agentic AI requires profound shifts in organizational structure, talent, and commercial models:

• GTM teams now routinely embed 2–3 engineers per marketer to manage agent orchestration, integrations, and rapid experimentation cycles.
• Hybrid pricing models blending seat licenses, token consumption, and outcome-based payments align vendor economics closely with AI usage and realized business impact.
• Prompt portability and modular multi-agent architectures have emerged as best practices, allowing reusable AI instructions and knowledge transfer that reduce retraining costs and mitigate vendor lock-in.
• Contracting increasingly resembles outsourcing, embedding SLAs, compliance guarantees, and auditability provisions to ensure AI decision quality and risk mitigation.
• Embedded governance copilots dynamically enforce compliance, crucial for regulated industries and enterprise risk management.
• These shifts produce engineering-driven, data-informed GTM organizations capable of disciplined innovation and rapid scaling of AI-driven revenue operations.

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New Supporting Signals: AI-Enabled Account-Based Marketing, Discovery Calls Evolution, and C-Suite Playbook Rewrites

Recent insights from complementary domains further illuminate agentic AI’s transformative impact on B2B GTM:

• AI-enabled Account-Based Marketing (ABM) at scale is revolutionizing how enterprises identify, engage, and convert high-value accounts. AI automates personalized outreach, dynamic segmentation, and campaign orchestration, transforming ABM from niche strategy to mainstream GTM pillar.
• The traditional discovery call is rapidly becoming obsolete in AI-native sales motions. Autonomous agents and AI-driven buyer profiling enable pre-call qualification and contextual engagement, reducing human sales effort and accelerating deal progression.
• AI is rewriting the B2B marketing playbook for CIOs, CTOs, and CMOs, shifting leadership focus toward AI governance, infrastructure investment, and cross-functional orchestration to harness AI’s full revenue potential.

These trends emphasize that AI’s disruption extends beyond tools to the very processes and mindsets defining B2B GTM.

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Strategic Recommendations for B2B GTM Leaders

To capitalize on agentic AI’s transformative potential, B2B GTM leaders must:

• Architect GTM motions fully around agentic AI, embedding autonomous agents across all revenue functions—from account-based prospecting to deal closing and customer success.
• Invest aggressively in inference-efficient hardware and real-time data platforms to optimize latency, cost, and regulatory compliance.
• Adopt hybrid monetization and API economy models that align costs with actual AI usage and measurable business impact.
• Design for prompt portability and modular orchestration to safeguard AI knowledge assets and maintain vendor flexibility.
• Operationalize AI-driven account planning, pipeline orchestration, and embedded governance copilots to ensure compliance and accountability.
• Expand engineering talent and foster disciplined experimentation to accelerate innovation and avoid vendor lock-in.
• Leverage democratization platforms like SolveAI and training tools such as Guidde to scale adoption and employee proficiency.
• Incorporate verticalized agents (e.g., Harper in insurance, Sherpas in wealth management, Kinfolk in HR, Basis in accounting) to embed domain expertise and compliance.
• Embed AI agents directly into core workflows—as Atlassian’s Jira agents demonstrate—to enable seamless human-AI collaboration.
• Integrate emerging trust layers from providers like t54 Labs to enforce governance, auditability, and risk mitigation.

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Conclusion: Agentic AI Defines the Future of B2B GTM Success

The convergence of verticalized AI agents, enterprise-grade AI-native platforms, next-generation hardware infrastructure, democratized agent creation, and robust trust frameworks has firmly established agentic AI as the defining architecture of modern B2B GTM success in 2028.

Legacy SaaS models face rapid displacement by agent-to-agent commerce and modular orchestration layers that unlock unprecedented unit economics, buyer engagement, and durable competitive moats. Evolving monetization, governance, and contracting paradigms accelerate this transformation.

The mandate for B2B GTM leaders is unequivocal and urgent:
Fully integrate, govern, and operationalize agentic AI throughout the revenue lifecycle to accelerate pipeline growth and build enduring market leadership in an AI-driven future. Those who embrace this transformation today will shape the winners of tomorrow’s B2B marketplace.