The Complete Guide to AI Sales Enablement (2026)
Everything you need to know about modern sales enablement: strategy, AI tools, best practices, technology stack selection, ROI measurement, and the future of AI-powered selling. Consolidating 7+ guides into one definitive resource.
Table of Contents
What is Sales Enablement?
Sales enablement is the strategic, ongoing process of equipping your revenue teams with the content, tools, training, coaching, and data they need to engage buyers effectively at every stage of the purchasing journey. It is the connective tissue between marketing strategy and frontline sales execution -- the discipline that ensures the right message reaches the right buyer at the right moment.
The concept has evolved dramatically from its origins as a content management function in the early 2010s. Today, sales enablement encompasses AI-powered coaching, conversation intelligence, predictive analytics, generative content creation, and real-time buyer engagement tracking. It has become the central nervous system of modern revenue organizations.
Why Sales Enablement Matters Now
The business case for sales enablement has never been stronger -- or more urgent. Consider the current landscape:
- Sales-marketing misalignment costs $1 trillion annually across the global economy. Enablement bridges this gap by creating shared content strategies, unified messaging, and closed-loop analytics.
- 90% of marketing content goes unused by sales teams. This is not a content creation problem -- it is a content discovery and relevance problem that AI-powered enablement solves.
- Only 35% of a sales rep's time is spent actually selling. The remaining 65% goes to administrative tasks, content searching, CRM updates, and meeting preparation. AI automation reclaims this time.
- Average sales rep turnover is 34%. Without enablement infrastructure, institutional knowledge walks out the door with every departure. AI-captured best practices persist across the organization.
The organizations that invest in enablement see compound returns: higher win rates, faster ramp times, better content utilization, and more predictable revenue. Those that don't are losing ground to competitors who have made enablement a strategic priority.
For a deeper framework on building enterprise AI strategy that encompasses sales enablement, see our Complete Enterprise AI Strategy Guide.
The AI Revolution in Sales (2025-2026)
Artificial intelligence is not enhancing sales enablement -- it is fundamentally reconstructing it. Between 2024 and 2026, every major category within sales enablement has been transformed by AI capabilities that were theoretical just three years ago. Here is how each dimension is evolving.
Conversation Intelligence
Platforms like Gong, Chorus (ZoomInfo), and Clari now analyze every sales call, meeting, and email interaction. These systems achieve 84% predictive accuracy for deal outcomes based on conversation patterns -- identifying winning behaviors (optimal talk-to-listen ratios, effective objection handling, competitor mention strategies) and coaching reps to replicate them. The technology has evolved from post-call analysis to real-time in-call guidance, providing live suggestions during active conversations.
AI-Powered Coaching
AI coaching engines are producing remarkable results: reps who receive AI coaching are 35% more likely to increase deal size, and organizations deploying AI coaching have reduced new hire ramp time from an average of 9 months to 5.8 months -- a 36% reduction that directly impacts revenue capacity. Unlike human coaching (limited by manager bandwidth), AI coaching scales to every rep on every deal without incremental cost.
Predictive Analytics
AI-powered forecasting has achieved up to 96% accuracy in predicting deal outcomes, compared to the industry average of 47% for manual forecasting. This 35% improvement in forecast accuracy transforms pipeline management from guesswork into data-driven precision. CFOs and CROs can now plan capacity, hiring, and resource allocation with confidence that simply was not possible before.
Content Personalization
AI-driven content personalization delivers 25% higher email performance and 41% higher SMS click-through rates. Instead of sending the same deck to every prospect, AI analyzes buyer behavior, industry, deal stage, and competitive landscape to recommend or generate the exact content each stakeholder needs. This is not segmentation -- it is individualization at scale.
Generative AI
78% of sales technology vendors are now releasing AI features, and generative AI is the fastest-adopted capability. From automated proposal drafts to personalized follow-up emails to competitive battle cards generated in real-time, generative AI is eliminating the most time-consuming tasks in a sales rep's workflow. Gartner projects that by 2027, 95% of all seller research will begin with AI.
"By 2028, 90% of B2B buying interactions will be intermediated by AI agents."
-- Gartner, 2025The B2B Buyer Journey in the AI Era
The traditional sales funnel is dead. In the AI era, B2B buyers have fundamentally changed how they research, evaluate, and purchase solutions. Understanding this transformed journey is essential for any sales enablement strategy.
The New Buyer Reality
Today's B2B purchase involves an average of 6-10 decision makers per deal. Forrester's latest research pushes this even higher: up to 13 internal stakeholders and 9 external advisors influence a single enterprise purchase. Each stakeholder consumes an average of 13 pieces of content before making a decision.
Perhaps the most striking finding: 95% of the time, the winning vendor was already on the buyer's day-one shortlist. This means the battle is not won during the sales conversation -- it is won during the anonymous research phase when buyers are forming their shortlist. Sales enablement must equip organizations to be visible, credible, and compelling before any human interaction occurs.
The 9-Stage Buyer Journey Framework
The modern B2B buyer journey spans nine distinct stages, each requiring different content and engagement strategies:
Awareness
Buyer identifies a pain point or opportunity. Content: thought leadership, industry reports, educational blog posts.
Interest
Buyer begins exploring solutions. Content: webinars, guides, comparison articles, podcasts.
Consideration
Buyer builds their shortlist. Content: case studies, ROI calculators, product demos, analyst reports.
Evaluation
Buyer compares finalists. Content: competitive battle cards, technical documentation, security whitepapers.
Decision
Buyer makes the purchase decision. Content: proposals, pricing, ROI business cases, executive summaries.
Purchase
Transaction and contract execution. Content: implementation guides, onboarding plans, SLAs.
Adoption
Buyer begins using the solution. Content: training materials, quick-start guides, best practices.
Expansion
Buyer grows usage across teams. Content: advanced feature guides, expansion business cases, new use cases.
Advocacy
Buyer becomes a champion. Content: review requests, referral programs, community engagement, co-marketing.
Content Strategy by Funnel Stage
| Funnel Stage | Buyer Need | Content Types | Enablement Role |
|---|---|---|---|
| TOFU (Top of Funnel) | Education & awareness | Blog posts, social content, industry reports, webinars | SEO optimization, thought leadership distribution |
| MOFU (Middle of Funnel) | Evaluation & comparison | Case studies, ROI calculators, product demos, battle cards | Content recommendation, competitive intelligence |
| BOFU (Bottom of Funnel) | Decision & justification | Proposals, pricing, executive summaries, implementation plans | Proposal automation, deal coaching, stakeholder mapping |
Calculate your team's potential productivity gains with our interactive sales productivity calculator.
The AI Strategy Blueprint
The definitive guide to enterprise AI strategy — covering the 10-20-70 rule for AI investment, governance frameworks, ROI quantification, and the crawl-walk-run deployment methodology. Essential reading for sales leaders navigating AI transformation.
10 Best Practices for AI Sales Enablement
These ten practices synthesize the most effective strategies from hundreds of enterprise deployments, updated for the AI-first era of 2026.
Align Sales and Marketing Around AI
The $1 trillion annual cost of sales-marketing misalignment stems from disconnected content strategies, conflicting buyer messaging, and siloed analytics. AI-powered enablement platforms create a shared operating layer: marketing sees which content sales actually uses (and which they ignore), while sales gets AI-curated content matched to deal context. Start by establishing a joint content council that meets bi-weekly and uses AI analytics to drive content creation priorities.
Build an AI-First Content Strategy
90% of sales content goes unused -- the largest waste in most marketing budgets. The solution is not creating more content but creating smarter content. Deploy AI content analytics to identify which assets actually influence deals, then use generative AI to create variations optimized for specific industries, buyer personas, and deal stages. Every content asset should be tagged, searchable, and AI-recommended based on deal context.
Deploy AI Coaching at Scale
Human coaching is essential but unscalable. The average sales manager has 8-12 direct reports and can observe maybe 2-3 calls per rep per quarter. AI coaching observes every interaction, identifies patterns across the entire team, and provides personalized guidance. Organizations using AI coaching report 35% larger average deal sizes and 5.8-month ramp times (down from 9 months).
Invest in Conversation Intelligence
Conversation intelligence is the single highest-ROI investment in modern sales enablement. Recording, transcribing, and analyzing every customer interaction creates an organizational memory that compounds over time. Winning patterns become visible, objection handling improves systematically, and forecast accuracy jumps from 47% to over 80%. The data also feeds back into marketing, product, and customer success for cross-functional improvement.
Map Content to Every Buyer Journey Stage
With 13 internal and 9 external stakeholders per deal, each consuming 13+ pieces of content, your enablement program must deliver role-specific content at each of the nine buyer journey stages. Build a content matrix: buyer persona on one axis, journey stage on the other. Identify gaps (most organizations are strong at TOFU but weak at MOFU/BOFU) and use AI to generate first drafts for missing assets.
Create a Single Source of Truth
When reps cannot find the right content, they create their own -- often with outdated messaging, non-compliant claims, or incorrect pricing. A centralized, AI-searchable content hub eliminates this risk. Implement version control, approval workflows, and automatic expiration for time-sensitive materials. The platform should be the first place reps look, not the last resort.
Train Continuously with Adaptive Learning
87% of training skills are lost within 30 days without reinforcement. Replace annual kickoff training with continuous micro-learning: 5-10 minute daily modules delivered through AI that adapts to each rep's skill gaps, deal context, and learning pace. Training delivers 353% average ROI when it is continuous rather than event-based.
Measure What Matters (Not Vanity Metrics)
Stop measuring content downloads and start measuring content influence on revenue. The metrics that matter: content-to-close correlation, time-to-first-deal for new hires, win rate by enablement engagement level, content utilization rate (percentage of assets used in won deals), and seller confidence scores. If a metric does not connect to revenue, it is a vanity metric.
Choose the Right Technology Stack
The average enterprise uses 5-8 point solutions for sales enablement. This fragmentation creates data silos, user fatigue, and integration nightmares. Consolidate toward 2-3 integrated platforms. Evaluate on six criteria: ease of use, CRM integration depth, AI capability maturity, content management rigor, analytics depth, and security/compliance certifications. See Chapter 5 for the full evaluation framework.
Start Small and Scale (Crawl-Walk-Run)
The organizations with the highest AI penetration in sales started with the smallest initial deployments. Begin with a single team, a single use case, and a 60-day proof of value. Demonstrate ROI before expanding. The crawl-walk-run framework: Crawl -- deploy AI content search for one team; Walk -- add conversation intelligence and coaching; Run -- full platform deployment with predictive analytics and automated workflows.
Building Your Sales Enablement Technology Stack
The sales enablement technology landscape is consolidating rapidly. The Highspot-Seismic merger in 2025 created a combined entity valued at over $6 billion, signaling that enablement has matured from a nice-to-have category into essential enterprise infrastructure. The trend is clear: organizations are moving from 5-8 point solutions toward 2-3 integrated platforms.
5 Core Platform Categories
Content Management & Intelligence
Central repository with AI-powered search, recommendations, and usage analytics. Tracks which content influences deals.
Conversation Intelligence
Records, transcribes, and analyzes sales calls. Identifies winning patterns and coaches reps in real-time.
Training & Coaching
Onboarding, continuous learning, certification, and AI-driven skill development platforms.
Sales Engagement
Multi-channel outreach orchestration with AI-optimized sequences, timing, and messaging.
Revenue Intelligence & Analytics
AI-driven forecasting, pipeline analytics, and deal scoring across the entire revenue engine.
Pricing Benchmarks by Company Size
| Company Size | Annual Budget | Typical Stack | Primary Focus |
|---|---|---|---|
| SMB (1-200 reps) | $5,000 - $15,000/yr | 1-2 platforms | Content management + basic analytics |
| Mid-Market (200-1,000 reps) | $30,000 - $75,000/yr | 2-3 platforms | Content + conversation intelligence + training |
| Enterprise (1,000+ reps) | $100,000 - $300,000+/yr | 3-5 integrated platforms | Full stack with AI coaching + predictive analytics |
6 Evaluation Criteria
| Criterion | Weight | What to Evaluate |
|---|---|---|
| Ease of Use | 25% | Rep adoption rate in pilot, time-to-value, mobile experience |
| Integration Depth | 20% | Native CRM connectors, API flexibility, SSO/SCIM support |
| AI & Automation | 20% | Content recommendations, generative AI, predictive scoring, coaching |
| Content Management | 15% | Version control, approval workflows, tagging, search quality |
| Analytics | 10% | Content influence on revenue, buyer engagement tracking, rep scorecards |
| Security & Compliance | 10% | SOC 2 Type II, GDPR, HIPAA, FedRAMP (if applicable) |
Get Chapter 1 Free + AI Academy Access
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AI-Powered Proposal & RFP Automation
Proposal and RFP response is where AI delivers the most immediate, measurable impact in sales enablement. The RFP automation market reached $0.9 billion in 2024 and is projected to grow to $2.43 billion by 2029, driven by organizations that have seen dramatic efficiency gains.
Case Study: Dell Technologies
Dell Technologies deployed AI-powered proposal automation across their enterprise sales organization and achieved remarkable results: $650M+ in opportunities processed through the system, 10X increase in proposal volume, and proposal creation reduced from 3-6 weeks to just 2 days. The system's AI engine matches RFP requirements to Dell's content library, generates compliant first drafts, and flags areas requiring human review -- transforming the proposal team from content creators into strategic reviewers.
The 5-Step Automation Process
- Intake & Analysis: AI parses the RFP/RFI document, identifies requirements, and categorizes questions by domain (technical, compliance, pricing, implementation).
- Content Matching: AI searches your content library and matches existing answers to RFP questions with confidence scores. High-confidence matches are auto-populated.
- Draft Generation: For questions without existing content, generative AI creates first drafts based on product documentation, past proposals, and competitive positioning.
- Human Review & Refinement: Subject matter experts review AI-generated content, focusing their time on strategic differentiation rather than first-draft creation.
- Assembly & Submission: AI formats the final proposal according to RFP specifications, generates executive summaries, and prepares submission packages.
RFP vs. RFI: Key Differences
| Dimension | RFP (Request for Proposal) | RFI (Request for Information) |
|---|---|---|
| Purpose | Solicit detailed proposals with pricing | Gather general information and capabilities |
| Detail Level | Comprehensive (technical, commercial, legal) | High-level capabilities and qualifications |
| Typical Length | 50-500+ pages | 10-50 pages |
| Response Time | 3-6 weeks (manual) / 2-5 days (AI) | 1-2 weeks (manual) / 1-2 days (AI) |
| AI Impact | 10-17X faster with 2.3X accuracy | 5-8X faster with standardized responses |
AI Tools Built for Sales Teams
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Blockify
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Training Your Sales Team on AI
The AI skills gap is the single largest barrier to sales enablement ROI. Technology is only as effective as the people using it, and the data is sobering: 59% of enterprise leaders report an AI skills gap in their organizations. IDC projects that skills shortages could cost the global economy $5.5 trillion by 2026.
The 4-Phase AI Training Framework
AI Literacy Foundations
What AI can and cannot do, prompt engineering basics, compliance guardrails, ethical use guidelines. Every employee should complete this phase.
Tool-Specific Training
Hands-on training with your chosen enablement platform. Role-specific use cases: SDRs focus on outreach, AEs on proposals, managers on coaching dashboards.
Supervised Practice
AI coaching during live deals with manager oversight. Review AI-generated proposals before sending. Build confidence through guided real-world application.
Continuous Reinforcement
Weekly micro-learning modules (5-10 minutes), AI-adapted to each rep's skill gaps. Quarterly certifications. Peer learning communities.
Iternal AI Academy
517+ AI courses designed for sales professionals, from beginner prompt engineering to advanced AI-powered selling techniques. Role-based curricula for SDRs, Account Executives, Sales Managers, and Revenue Leaders. Certifications aligned with EU AI Act Article 4 literacy mandates.
Explore AI AcademyMeasuring Sales Enablement ROI
Sales enablement ROI is not theoretical -- the data from best-in-class organizations is compelling and consistent across industries, geographies, and company sizes.
Key Performance Benchmarks
The Content Utilization Problem
65% of sales content is never used. This is the single largest inefficiency in most revenue organizations. Marketing creates assets that never reach buyers because reps cannot find them, don't know they exist, or don't believe they're relevant. AI-powered enablement solves this by automatically surfacing content based on deal context -- but only if you measure utilization and tie it to outcomes.
Practical ROI Formula
Sales Enablement ROI Calculator
For a personalized calculation based on your team's metrics, try our Sales Team Productivity Calculator.
Need Help Building Your AI Sales Enablement Strategy?
Our AI Strategy Consulting team helps sales organizations implement AI-powered enablement programs.
Masterclass
AI sales strategy training and enablement program design
AI Strategy Sprint
6-week sales enablement transformation with technology selection
Transformation Program
End-to-end sales AI deployment with ongoing optimization
Founder's Circle
Full enterprise sales transformation with dedicated team
The Future: AI Co-Sellers & Revenue Intelligence
The next wave of sales enablement is already arriving. By 2028, the boundary between human seller and AI assistant will blur to the point of indistinguishability in many buying interactions.
AI Co-Sellers & Autonomous Agents
54% of sellers have already used AI agents in their workflow, and Gartner projects that AI agents will outnumber human sellers 10:1 by 2028. These are not chatbots -- they are autonomous systems that research prospects, draft personalized outreach, schedule meetings, prepare pre-call briefings, generate proposals, and follow up after calls. The human seller's role shifts from execution to strategy, relationship building, and complex negotiation.
Revenue Intelligence Convergence
Sales enablement, conversation intelligence, revenue operations, and customer success are converging into a unified "revenue intelligence" layer. Instead of separate platforms with separate data, organizations will operate a single AI-powered revenue engine that optimizes the entire customer lifecycle -- from first touch through expansion and renewal.
Partner Enablement with Predictive Intelligence
Channel and partner enablement is the next frontier. AI will predict which partners are most likely to close specific deal types, automatically route leads to the best-matched partner, and provide partners with the same AI coaching and content intelligence that direct sales teams use. Predictive personalization in partner enablement is already demonstrating 3-4X higher engagement rates compared to generic partner communications.
The McKinsey Projection
"Generative AI could produce $2.6-4.4 trillion in enterprise economic impact annually, with sales and marketing representing one of the highest-value application domains."
-- McKinsey Global Institute, 2025The organizations that build their sales enablement infrastructure now will capture disproportionate value as these technologies mature. Those that wait will face the compounding cost of inaction: every year of delay transfers market share, talent, and institutional knowledge to competitors who moved first.
For a comprehensive framework on AI strategy beyond sales, see our Complete Enterprise AI Strategy Guide. The AI Strategy Blueprint covers the 10-20-70 rule for AI investment allocation that applies directly to sales enablement budgeting.
Master AI for Sales
517+ AI courses designed for sales professionals. From beginner prompt engineering to advanced AI-powered selling. Role-based curricula with certifications.
Explore AI AcademyAI Strategy Consulting
Expert guidance on building your AI-first sales enablement strategy. From readiness assessment to full implementation with measurable ROI.
Explore ConsultingThe AI Strategy Blueprint
The AI Strategy Blueprint provides the complete 16-chapter framework for enterprise AI transformation -- covering governance, ROI quantification, workforce training, and the 10-20-70 rule that determines whether AI investments produce returns. Essential reading for any leader building an AI-powered sales enablement strategy.
Evaluate Your Organization's AI Readiness
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Browse AI AssessmentsFrequently Asked Questions
Sales enablement is the strategic, ongoing process of providing your sales organization with the content, tools, training, and coaching they need to engage buyers effectively at every stage of the purchasing journey. Unlike CRM (which tracks deals) or marketing automation (which generates leads), sales enablement bridges the gap between marketing content creation and frontline sales execution. In 2026, modern sales enablement is AI-first: intelligent systems surface the right content at the right time, coach reps in real-time during calls, and automate proposal generation. Organizations with formal enablement programs achieve 49% higher win rates on forecasted deals.
AI is transforming sales enablement across five dimensions: (1) Conversation intelligence platforms like Gong and Chorus analyze every sales call with 84% predictive accuracy for deal outcomes; (2) AI coaching reduces ramp time from 9 months to 5.8 months and makes reps 35% more likely to increase deal size; (3) Predictive analytics improve forecast accuracy by up to 96%; (4) Content personalization drives 25% higher email performance; (5) Generative AI automates proposal creation, reducing 25+ hours to under 5 hours. Gartner predicts that by 2027, 95% of seller research will begin with AI, and by 2028, AI agents will outnumber human sellers 10:1.
Best-in-class sales enablement programs deliver measurable ROI across multiple dimensions: 49% higher win rates on forecasted deals, 84% quota attainment (vs. 60% without enablement), 40-50% reduction in ramp time for new hires, and 23% more competitive deal wins. The practical ROI calculation: if your average deal size is $50,000, your team closes 100 deals/year, and enablement improves win rates by 15%, that produces $750,000 in incremental revenue. Against a typical $100K-$300K platform investment, ROI ranges from 150% to 650% in year one alone.
Implementation timelines vary by scope: a basic content management platform deploys in 4-8 weeks; conversation intelligence requires 6-12 weeks including CRM integration and call recording setup; a comprehensive enablement platform with AI coaching, content analytics, and training takes 3-6 months. The crawl-walk-run approach works best: start with a single use case (content search or call recording) for one team, demonstrate ROI within 60 days, then expand. Organizations that try to deploy everything at once experience 3x higher failure rates than those that sequence deliberately.
CRM (Customer Relationship Management) tracks deals, contacts, and pipeline data after sales interactions occur. Sales enablement equips reps before and during those interactions. CRM answers "where is the deal?" while enablement answers "how do I win the deal?" The two are complementary: CRM provides the data backbone, and enablement layers on content recommendations, coaching insights, competitive intelligence, and training. In practice, 72% of organizations use their CRM as the system of record but rely on a separate enablement platform for content management, training delivery, and engagement analytics.
Evaluate platforms across six criteria: (1) Ease of use -- if reps will not adopt it, ROI is zero; (2) CRM integration depth -- native Salesforce/HubSpot connectors, not just API access; (3) AI capabilities -- look for conversation intelligence, content recommendations, and generative AI built in, not bolted on; (4) Content management -- version control, approval workflows, and usage analytics; (5) Analytics -- buyer engagement tracking, content performance, and rep activity dashboards; (6) Security and compliance -- SOC 2 Type II, GDPR, and industry-specific certifications. Budget ranges: SMB $5-15K/year, mid-market $30-75K/year, enterprise $100-300K+/year.
Follow a structured 4-phase approach: Phase 1 (weeks 1-2) -- AI literacy basics: what AI can and cannot do, prompt engineering fundamentals, and compliance guardrails. Phase 2 (weeks 3-4) -- tool-specific training on your chosen platform with role-specific use cases. Phase 3 (months 2-3) -- supervised practice with AI coaching during live deals. Phase 4 (ongoing) -- continuous reinforcement with weekly micro-learning. Research shows 87% of training skills are lost within 30 days without reinforcement, so the ongoing phase is critical. Iternal AI Academy offers 517+ AI courses designed for sales professionals with adaptive learning paths.
Conversation intelligence is AI-powered technology that records, transcribes, and analyzes sales calls and meetings to extract actionable insights. It identifies patterns in winning deals (talk-to-listen ratios, competitor mentions, objection handling), coaches reps with real-time suggestions, and predicts deal outcomes with up to 84% accuracy. The technology has moved from post-call analysis to real-time in-call guidance. Major platforms include Gong, Chorus (acquired by ZoomInfo), and Clari. Organizations using conversation intelligence see 35% improvement in deal sizes and 28% faster deal cycles.
AI is fundamentally restructuring the B2B buyer journey: 89% of B2B buyers now use generative AI as their primary research tool, 80% of the buying journey is completed before contacting a sales rep, and 61% of buyers prefer a completely rep-free experience. The average B2B deal now involves 6-10 decision makers (Forrester says up to 13 internal and 9 external stakeholders), each consuming an average of 13 pieces of content before a decision. Critically, 95% of the time the winning vendor was already on the buyer's day-one shortlist. This means sales enablement must focus on being found and credible during the anonymous research phase, not just the sales conversation.
In 2025, Highspot and Seismic -- the two largest standalone sales enablement platforms -- announced a merger creating a combined entity valued at over $6 billion. This consolidation reflects a broader industry trend: the average enterprise uses 5-8 point solutions for sales enablement, and the market is converging toward 2-3 integrated platforms. For buyers, this means fewer vendor choices but more comprehensive functionality per platform. For the industry, it signals that sales enablement has matured from a nice-to-have category into essential enterprise infrastructure, similar to how CRM consolidated around Salesforce in the 2010s.