AI Adoption in Partner Ecosystems: What Partner and GTM Executives Are Thinking, Asking, and Searching for
Highlights
According to a Forrester’s survey, most B2B partner and channel marketing decision‑makers expect the number of partners to grow, with the strongest expansion expected from technology partners, distribution partners and digital routes to market
Salesforce’s SMB survey notes that 74% of growing SMBs are increasing data management investments, compared with 47% of declining SMBs.
Partner leaders are adopting AI tools by building custom GPTs to automate tasks such as reading long legal documents, summarizing training sessions and meeting notes, and drafting RFPs.
7 things AI can help you track and measure for success.
See a map of partner‑related functions to their most common AI use cases and associated benefits.
Microsoft saw a 200% increase in partner organizations with Azure AI specializations since January 2024; partners deriving ≥25% of revenue from Microsoft AI grow revenue at double the rate of those deriving less than 25%.
Introduction
As partner and sales executives look to the future, the ground is shifting under their feet. The partner ecosystem is expanding at a pace few anticipated: two‑thirds of B2B leaders expect partner‑influenced revenue to grow by more than 30% year over year and 67% plan for indirect revenue to jump by more than 30% according to Forrester’s Partner Ecosystem Marketing Survey. At the same time, generative AI has stormed into the boardroom, promising to automate prospecting, personalize outreach and streamline joint selling.
Yet the story isn’t all rosy. The 2025 Generative AI Adoption in the Enterprises survey by Writer reveals that 42% of executives feel generative AI adoption is tearing their company apart, and 68% report friction between IT and the rest of the organization. In other words, the very technology that could accelerate your pipeline is also causing cultural rifts and governance headaches. This report distills what partner and GTM professionals are thinking, asking and googling right now—so you can harness AI’s upside without losing your grip on trust, alignment, and partner relationships.
Subscribe to AI Partnerships Insights to get weekly roundups, deep dives, toolkits, and more.If last week’s partner news felt like a firehose, that’s because it was. In just five days we saw Palo Alto tighten its partner grip, Meta throw ten billion at Google Cloud, Appian bring in a heavyweight to scale alliances, and Reliance try to position itself as the AI operating system of India. Layer in Hexaware cozying up to Replit, Okta stretching into PAM, and trailBlazer6 dropping AI agents straight into revenue ops, and you’ve got a week that tells us two things. First, security and identity are quietly becoming the backbone of every serious GTM motion. Second, AI adoption isn’t about apps anymore — it’s about who you’re connected to, and which ecosystem you orbit. Below is the breakdown of what happened, why it matters, and how partner leaders should be thinking about their next moves.
The state of AI adoption and sentiment
Adoption momentum
Broad but uneven adoption. ICONIQ’s State of GTM 2025 report notes that 70% of companies report moderate or full AI adoption in GTM workflows, with top use cases including meeting transcription, lead generation and content creation. Microsoft’s partner ecosystem survey (March 2025) finds that more than 60% of organizations have implemented at least three generative AI use cases and that 80% of early projects fail due to complexity. Salesforce’s SMB survey of 3,350 leaders shows that 75% of SMBs are experimenting with AI and 91% of those using AI say it boosts revenue.
Productivity gains with caveats. In LexisNexis’s Future of Work 2025 study, 53% of knowledge workers save one to two hours per day thanks to generative AI and 30% save three to four hours. A recent survey found that 58% of executives report exponential productivity or efficiency gains and 16% say AI frees knowledge workers from repetitive tasks. However, the same survey warns that only 37% of organizations now consider themselves data‑ and AI‑driven, down from 48% the year before, and 92% cite cultural and change‑management issues as the main barrier. That echoes Writer’s data: 72% of AI projects are developed in silos.
Optimism tempered by trust issues. LexisNexis reports that 82% of professionals are open to adopting generative AI and 73% believe it will positively impact their daily work. Yet 47% worry about data privacy/security and 44% lack trust in AI outputs. The IAB State of Data 2025 survey adds that only 30% of agencies, brands and publishers have fully integrated AI across the media campaign lifecycle, while half of the industry lacks a strategic roadmap. Nearly two‑thirds cite data quality, data protection and tool fragmentation as top barriers.
C‑suite tension. Writer’s Enterprise AI Adoption report highlights that 42% of C‑suite executives say generative AI is tearing their company apart, signalling tension between business and technology leadership. According to the same report, 68% report friction between IT and other departments and 72% of AI applications are built in silos. Writer’s analysis also notes that companies with a formal AI strategy have an 80% success rate, while those without achieve only 37%.
AI adoption within partner ecosystems
Expanding partner ecosystems. Forrester’s Partner Ecosystem Marketing Survey finds that most B2B partner and channel marketing decision‑makers expect the number of partners to grow, with the strongest expansion expected from technology partners, distribution partners and digital routes to market. Moreover, 67% expect indirect (partner‑transacted) revenue to grow above 30% and two‑thirds expect partner‑influenced revenue to grow above 30%. Forrester concludes that organizations must invest in partner ecosystem strategy and supporting functions to drive AI innovation and growth.
Marketplace dependency and confidence gap. A Futurum Group survey shows that 97% of channel partners derive revenue through hyperscaler marketplaces and 34% obtain more than 10% of their revenue from them. 46% of partners feel extremely confident about succeeding amid AI transformation, yet only 20% believe they have a strong reputation in AI.
Program changes and specializations. SAP has re‑engineered its PartnerEdge program to be 100% cloud‑focused, encouraging partners to innovate on SAP’s AI portfolio and aligning incentives with adoption‑led growth. Microsoft’s March 2025 survey reports a 200% increase in partner organizations with Azure AI specializations since January 2024; partners deriving ≥25% of revenue from Microsoft AI grow revenue at double the rate of those deriving less than 25%.
What partner and GTM professionals are asking
Partner leaders, GTM managers and functional executives are grappling with how to move from experimentation to strategic execution. Common questions include:
How do we align cross‑functional teams and avoid silos? The high rate of friction between IT and line‑of‑business teams, as highlighted in Writer’s survey, underscores the need for clear governance, executive sponsorship and integrated roadmaps. Questions often revolve around building formal AI strategies, obtaining budgets and aligning incentives.
Which AI use cases deliver the highest ROI? ICONIQ’s report lists meeting transcription, lead generation and content creation as the most common GTM use cases. The G2 AI adoption survey shows that 69% of organizations have adopted chatbots or virtual assistants; marketing teams are leading adoption, with 79% of buyers prioritizing AI capabilities when selecting software. Salesforce’s SMB survey notes that SMB leaders emphasize marketing campaign optimization, content generation, automated recommendations and natural language search as top applications.
How do we measure success? AlphaBOLD’s benchmark survey found that while many executives report productivity gains, companies rarely measure outcomes rigorously. Goldman Sachs saw only a 20% productivity boost among developers using generative AI. Partner leaders ask how to quantify efficiency gains, tie AI initiatives to revenue and avoid inflated expectations.
How do we ensure data quality and trust? LexisNexis highlights data privacy and security concerns. Salesforce’s SMB survey notes that 74% of growing SMBs are increasing data management investments, compared with 47% of declining SMBs. The IAB State of Data 2025 finds that two‑thirds of agencies cite data quality and protection as barriers. Questions focus on building modern data foundations, managing unstructured data and implementing AI governance.
What training and certifications do we need? A surge in Microsoft AI specializations reflects a race for skills. Partner programs like SAP PartnerEdge place AI innovation at the center. Professionals ask which certifications matter, how to train partner managers and how to reskill pre‑sales engineers.
How do we balance automation with human relationships? AI can automate partner inquiries and personalize engagement but warns that AI augments rather than replaces human connection. It’s wise to caution against over‑reliance on AI, stressing the need to maintain human oversight even as hyper‑personalization and chatbots improve efficiency. Being an “AI passenger” erodes critical thinking and that professionals should remain active drivers.
How do we embed governance and ethics into partner offerings? Credo AI emphasizes building trusted AI ecosystems where governance is integrated into workflows, enabling partners to evaluate fairness and toxicity at the use‑case level. They claim that services partners see 10×–15× pull‑through revenue for every dollar of Credo AI software, highlighting the commercial upside of responsible AI.
How do we prepare for AI agents and multimodal models? Microsoft predicts that most organizations will move from generic SaaS models to custom AI workloads within 24 months, and that generative AI agents will become central to digital experiences. Deloitte’s global predictions, cited by AlphaBOLD, estimate that a quarter of enterprises employing generative AI will deploy AI agents by 2025. Professionals want to know when to adopt agents, which workflows to automate, and how to ensure alignment between vendor tools and partner offerings.
Use cases and success stories
Marketing and sales acceleration. G2’s survey reports that organizations using AI for lead scoring, email drafting and chatbots see improved conversion rates and positive ROI, with 83% of companies that purchased an AI solution in the last three months reporting a positive return. Salesforce’s SMB survey notes that 87% of SMBs using AI say it helps them scale operations and 86% see improved margins. Marketing teams are using AI to decrease unsubscribe rates through automated list management and to personalize content at scale.
Partner enablement and co‑marketing. AI tools can support partner teams in a variety of ways. Partner Account Managers and the Marketing team can save time when crafting personalized emails that position the Partner Program or new launches. It can help analyze partner data to recommend optimal resource allocation and deliver on‑demand training. They can reduce the time to answer partner inquiries, and accelerate co‑marketing by adjusting messaging based on performance and other factors. Although hyper‑personalized partner training and marketing campaigns can be delivered via AI - for example by role or objective - human oversight remains essential. It’s a smart move for partner leaders to enable their managers to explore AI tools and workflows, for example by building custom GPTs to automate tasks such as reading long legal documents, summarizing training sessions and meeting notes, and drafting RFPs. These are just a few examples of the practical applications of AI and we will explore more in the coming weeks and months on AI Partnership Insights.
Financial planning and analysis (FP&A). Finance leaders in the FP&A Trends survey say that only 35% of FP&A time is spent generating insights and that AI can automate reporting and enable real‑time analytics. FP&A leaders emphasise that AI will augment, not replace, their roles, and that storytelling skills are essential. This resonates with partner finance teams seeking to shift from manual reporting to strategic decision‑support.
Advertising and media. The IAB State of Data 2025 report shows that only 30% of advertising players have fully integrated AI across campaigns, but nearly half of those laggards expect to catch up by 2026. Data quality, protection and tool fragmentation are cited as barriers. Transparency issues are also pronounced: 50% of brands worry about how agencies use AI, and 50% of agencies worry about brands bringing AI capabilities in‑house. These concerns mirror partner managers’ worries about losing control when AI automates joint marketing.
Looking for examples of AI-powered partner programs? Read our latest roundup on what top tech companies are doing with AI-powered partner programs, from incentives to co-sell enablement. See the programs AWS implemented in 1H, 2025. |
What AI Can Help You Track and Measure for Success
AI can streamline how you track, analyze, and optimize partner performance across the funnel. Focus on these key metrics:
Partner Activation & Onboarding
Track time-to-activation, onboarding completion rates, and initial deal velocity with AI-enabled workflows.Training & Certification Progress
Monitor partner learning paths, certification status, and enablement milestones in real-time.Campaign Engagement & Execution
Use AI to assess partner-led campaign performance, including open rates, leads generated, and follow-through execution.Partner-Sourced & Influenced Revenue
Attribute pipeline accurately with AI-assisted attribution models — flag partner-sourced vs. co-sell impact.Co-Selling Outcomes
Analyze deal stage acceleration, win rates, and sales cycle improvements tied to joint selling motions.Internal Sales and AE Engagement
Set up dashboards to pull reports and analyze deal data
Partner Manager Effectiveness
Leverage AI to score QBR inputs, partner health metrics, and engagement quality at scale.
Download our mini-guide below. |
AI applications across partner-related teams
Partner-related functions—including marketing, partner recruitment, enablement, sales, pre‑sales, strategy, partner experience and partner portal teams—are already putting AI to work in very practical ways. The following examples highlight how individuals and teams are using AI to accelerate partner‑centric initiatives:
Recruiting and integration. Partner recruiting teams use generative models to scan and rank potential partners. One channel team combined GPT‑4 with LinkedIn Sales Navigator to score target profiles and saw a 40%+ increase in response rates for recruiting outreach. Integration teams at Apicbase rely on AI to analyze customer usage data and feature requests; this allowed them to launch integrations 30% faster and drove an 18% improvement in partner satisfaction.
Program management and prioritization. Partner managers can track partner activity, engagement and productivity in a more independent way. They train AI agents on portal and CRM data to surface high‑priority tasks—such as deal registrations needing attention and follow up, or partners who are less active in the portal.
Communications and Marketing. Partner managers and other teams use AI to generate content ideas and brainstorm, help create campaign copy and co‑marketing concepts, saving time and leveraging new ideas. AI also helps adjust messaging in joint campaigns based on performance data and segment analysis.
Upsell and cross‑sell. AI analyzes customer behavior, support interactions and product usage to suggest personalized upsell and cross‑sell paths. It identifies support issues that often precede expansion and recommends new services or content accordingly.
Onboarding and support. AI assistants embedded in partner portals deliver quick‑start guidance based on partner region or type, remind partners to complete onboarding steps and answer questions about program status, certifications, SPIFFs or marketing development funds. These bots free partner managers from repetitive queries while providing personalized support.
Enablement and relationship management. AI‑powered enablement and partner relationship management (PRM) platforms segment partners and deliver role‑based learning tracks. They can suggest follow‑ups based on partner activity and preferences and automatically produce dynamic dashboards that forecast deal velocity and track and report on partner engagement. AI is being used to accelerate partner onboarding by creating personalized training modules and interactive guidance, as well as improving partner activation.
Co‑selling. AI generates joint business plans and campaign drafts, recommends language tailored to specific persona, and market segments. It can help coordinate co‑selling motions across enablement, marketing, pre‑sales and partner teams.
Sales and pre‑sales enablement. Sales organizations report that AI adoption boosts productivity and deal outcomes. According to Highspot’s State of Sales Enablement 2025, 90% of companies have implemented or plan to implement AI; organizations with integrated enablement tech stacks are 42% more likely to increase sales productivity, and using AI for training increases the average deal size by 35% while AI‑driven coaching improves revenue outcomes by 20%. Pre‑sales teams use AI to draft proposals in minutes rather than weeks.
To summarize the breadth of applications, the table below maps partner‑related functions to their most common AI use cases and associated benefits.
Function | AI use case | Benefits and metrics |
Recruiting & integration | Partner profile scoring; integration opportunity discovery | 40%+ higher response rates; 30% faster integration launches and 18% higher partner satisfaction. |
Program management | Prioritizing tasks using portal/CRM data | Streamlined workflows; proactive issue resolution. |
Marketing & thought partnership | Content brainstorming; personalized campaign messaging | Time savings and creative lift. |
Upsell & cross‑sell | Analyzing behavior to recommend expansions | Personalized recommendations; increased expansion revenue. |
Onboarding & support | AI guides and chatbots in partner portals | Faster activation; reduced support load. |
Enablement & relationship management | Personalized training; follow‑up suggestions; forecasting | Better retention; more accurate forecasting |
Co‑selling & joint messaging | Generating joint business plans and co‑marketing content | Shorter planning cycles; targeted messaging |
Sales & pre‑sales | AI‑driven training, coaching and proposal generation | 42% higher productivity; 35% larger deals; 20% better revenue outcomes |
Budget, talent and operating model impacts
Rebalancing budgets. Forrester’s B2B Brand and Communications Survey 2025 reveals that investment in website/digital programs dipped from 64% to 60% of marketers, largely because generative AI enables teams to do more with less. Investment in content and creative services decreased from 53% to 44%, reflecting reliance on AI for content generation. In contrast, brand management investment increased from 42% to 52%, highlighting a renewed focus on brand differentiation when AI automates execution. Headcount expectations are flat or declining for digital and creative functions, signalling that AI is enabling leaner operations.
Training and upskilling. Microsoft’s survey reports a 200% increase in Azure AI specializations among partners since January 2024 and notes that partners earning ≥25% of revenue from AI grow at double the rate of those earning less. This underscores the value of investing in certifications, data science skills and prompt‑engineering capabilities for partner managers, sales engineers and marketing teams.
Cultural shift required. WorkSpan argues that AI adoption in partner teams is primarily a leadership and culture challenge. Partner leaders should act as cultural architects who reward experimentation, map repetitive workflows to identify AI opportunities and establish sharing rituals to spread learnings. GrowthShuttle warns that over‑reliance on AI can erode critical thinking; professionals should remain “AI drivers,” actively interrogating AI outputs rather than letting the technology do all the thinking.
Emerging themes and insights
Data quality and governance are now board‑level issues. Across surveys, poor data quality, fragmented tools and a lack of governance are the top inhibitors to scaling AI, as noted by the IAB State of Data 2025 report. Successful organizations invest heavily in data management — for example, 74% of growing SMBs are increasing data management investments according to Salesforce’s SMB survey — embrace unstructured data strategies and integrate AI governance into partner workflows. One example is Credo AI’s integration with Microsoft’s Azure AI Foundry, which surfaces fairness and toxicity metrics within developer workflows.
Strategic experimentation vs. silver‑bullet thinking. Many leaders are experimenting with AI without clear hypotheses; the AlphaBOLD survey notes that few organizations measure outcomes rigorously. The divide between AI optimists and skeptics will persist until executives adopt controlled experiments, define KPIs and share results across partner teams. WorkSpan’s “Frontline AI” approach provides a pragmatic model: empower frontline managers to test AI in specific tasks and share learnings.
Partnerships shift from volume to precision. Credo AI’s channel leader stresses that transformation moves at the speed of trust and that they are building precision partnerships rather than volume. This reflects a broader trend: partner leaders seek high‑impact collaborations (e.g., with hyperscalers, GSIs and boutique firms) that embed AI governance and compliance into joint offerings. The ROI is compelling: services firms can see 10×–15× services pull‑through per dollar of AI governance software.
Generative AI agents are on the horizon. Deloitte’s predictions estimate that by the end of 2025 one‑quarter of enterprises using generative AI will have deployed AI agents, a share expected to double by 2027. Microsoft anticipates that organizations will shift to custom AI workloads within 24 months. Partner managers are exploring how AI agents can autonomously generate proposals, triage partner inquiries and recommend next actions without undermining human judgment.
Security and transparency remain non‑negotiable. The IAB State of Data 2025 study shows that half of brands worry about the transparency of how agencies use AI and half of agencies worry about brands developing AI in‑house. Salesforce’s SMB survey finds that 81% of SMB leaders would pay more for technology from trusted vendors. This trust premium extends to partner ecosystems; success will depend on embedding robust security and compliance into every AI initiative.
Analyst outlook
Partner and GTM professionals have embraced AI as both a growth engine and a potential minefield. Adoption is accelerating. According to ICONIQ’s State of GTM 2025 report, more than 70% of GTM teams already use AI in some form, and Forrester reports that 67% of B2B leaders expect partner‑influenced revenue to soar. At the same time, friction between departments, data‑quality issues and lack of strategic roadmaps threaten to derail momentum. The executive mood is a blend of optimism and anxiety: employees love the productivity gains, yet nearly half lack trust in AI outputs according to Lexis Nexis. C‑suite tension is palpable; Writer’s Enterprise AI Adoption report notes that 42% of leaders believe AI adoption is tearing their company apart.
Several actionable insights emerge for partner leaders:
Be an AI driver, not a passenger. Adopt AI intentionally; design experiments, measure results and integrate learning into partner enablement and marketing. Resist the temptation to blindly trust AI outputs — GrowthShuttle reminds us that professionals should remain “AI drivers,” actively interrogating AI outputs rather than letting the technology do all the thinking.
Invest in data and governance. Secure, high‑quality data is the lifeblood of AI. Strengthen data management (structured and unstructured), embed AI governance into partner workflows and choose partners that prioritize responsible AI. Credo AI demonstrates how integrating governance into developer workflows can surface fairness and toxicity metrics, while Salesforce’s SMB survey shows that 81% of SMB leaders pay more for trusted technology, underscoring the trust premium.
Empower frontline teams and foster a culture of experimentation. Encourage partner managers, marketers, finance and engineers to map repetitive workflows, test AI tools and share learnings. WorkSpan’s “Frontline AI” approach illustrates how to make success (and failure) visible across the organization; AI adoption is a cultural transformation, not just a technology project.
Prioritize high‑impact partnerships. Shift from a volume game to precision partnerships that deliver differentiated AI solutions, Credo AI does this by focusing on eight strategic partner lanes. Align with hyperscalers, GSIs and ISVs that share your governance standards and can help you build custom AI workloads, as emphasised in Microsoft’s partner guidance.
Focus on measurable outcomes. Define KPIs tied to revenue, partner satisfaction and efficiency. Track the time saved, opportunities generated and margins improved. Avoid hype by measuring the incremental value of AI against control groups, the AlphaBOLD survey warns that few organizations measure outcomes rigorously.
With careful planning, ethical frameworks and a willingness to experiment, partners and GTM professionals can turn AI from a source of anxiety into a catalyst for scalable, sustainable growth. The next few years will reward those who build trust into their ecosystems, invest in data foundations and empower their teams to become AI drivers. Those who wait risk seeing their partners, and their competitors, leapfrog ahead.
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