Hi there,

I started AI Partnerships Insights with a simple goal, to help partner and GTM leaders navigate AI, ecosystems, and their own careers. I try to keep the content practical and grounded in the realities of B2B tech, from VC backed startups to the hyperscalers.

In just 6 weeks, the LinkedIn newsletter has passed 1,400 subscribers, and aipinsights.com (the primary platform) is seeing open rates well above 75%. I am grateful for this start, and also very aware that this sets a high bar for what I send you next.

I’m still far from our goal: to reach thousands of partner leaders, from those in their first partner roles to the most experienced ones. You all have incredible learnings to share. And most importantly, to build a library of tools you can leverage to save time or make progress with your goals.

Since starting, I have a much deeper appreciation for everyone who puts out content, especially those who publish week after week. Showing up consistently with something useful is real work.

Thank you for supporting my work. I am constantly iterating on the format and the topics. If there is something you want more of, less of, or a blind spot I am not seeing, I want to hear it. You can take this quick survey, hit reply, or message me on LinkedIn. Your feedback directly shapes what I cover here.

A new study by DXC is yet another proof point that some parts of the market are stuck between AI ambition and execution reality.

Google Cloud is firing on all partnership cylinders.

We are continuing to see partnership models built around sharing and activating data. The S&P Global and Google Cloud deal is a good example of the kind of ‘hybrid partnerships’ we will see a lot more of. I shared a similar partnering model last week between the London Stock Exchange and OpenAI, check it out here. For incumbents with data and the partners in their ecosystems, this is how you can create value for customers and launch new products and services.

How does a modern “gold standard” partner program in B2B SaaS actually look? One with clear partner economics, a deep focus on adoption and customer success, strong partner operations, meaningful AI investments, and a tighter AWS SCA at the center of its ecosystem? I’ve recently met with Eva Schönleitner, Vice President, Worldwide Partnerships at Smartsheet. Learn about their journey to redesign their Partner Program here.

The job market is tough right now. However, I’ve never seen so many partner related roles at startups. Ping me if I can facilitate an introduction that can help you land a new role.

Do you ask AI about personal development late at night and early in the morning? Looks like a lot of people do. I am guilty of both. Learn what users ask AI and when, directly from a post by Mustafa Suleyman, CEO of Microsoft AI.

If you find this update valuable, pls share with your network today. Now let’s dive into this week’s announcements.

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Anthropic and Accenture launched a multi‑year partnership that includes a dedicated Accenture Anthropic Business Group, and training for about 30,000 Accenture employees on Claude. The focus is moving enterprise customers from pilots to production AI. ​

My take for partner and GTM leaders

Only a few days ago, Accenture announced a similar partnership with OpenAI (see my previous Weekly Rundown). Frontier model alliances are evolving into full ecosystem motions, with consulting, assets, and marketplaces wrapped around a core model partner. Your opportunity here is to attach your vertical IP to this motion.

Accenture gets 30,000 people experimenting with Claude across real client work, which means they will quickly see where it shines or breaks, and where new offerings can be created. Anthropic gets a constant stream of input from industry experts and their customers, which will shape the product roadmap and the “dream” agent scenarios. If you lead partnerships, make time for your partners’ input on your products, you don’t know the gems you’ll get yet and how their feedback can help shape differentiated offers you co-own. Partner size doesn’t matter here. I’ve seen some of the best ideas come from boutique partners.

Microsoft announced plans to invest US$17.5 billion in India for AI and cloud infrastructure, skills, and sovereign capabilities, calling it its largest investment in Asia.

At almost the same time, Amazon said it will invest over $35 billion across its Indian businesses by 2030, with AI-driven digitization, export growth, and job creation as the three pillars, on top of roughly $40 billion already invested.

Earlier this year, Google committed $15 billion to build a dedicated AI hub and a large data center campus in Visakhapatnam. Taken together, these moves add up to more than $67 billion of planned big-tech spend focused on cloud, AI, and data centers in one market.

My take for partner and GTM leaders

If you partner with hyperscalers and are looking for growth, consider where you want to expand next. Partners will plan on co‑building industry solutions with these cloud providers’ field teams and launching local AI practices in India. If you already work with them in other regions, this investment gives you a way to extend reference wins into India. You can leverage joint customer stories and wins in other regions to boost your campaigns.​

S&P Global and Google Cloud announced a multi‑year strategic partnership to accelerate S&P’s enterprise‑wide transformation across agentic innovation, data distribution, and workflow automation. The deal centers on unifying S&P’s proprietary data on BigQuery and using Gemini Enterprise as the agentic layer, so customers and employees can work with S&P’s “essential intelligence” through AI‑ready experiences.

​My take for partner and GTM leaders

AI has made owning large datasets even more valuable, especially if the way the data is accessible. What value can you extract from your data, your partners’ data, and your customers’ data? What products can you create? This playbook is valid at any scale, from the smallest startups to the largest institutions. Incumbents who sit on large volumes of valuable data want AI distribution without losing control of their crown‑jewel datasets. S&P is turning its content into AI‑ready products, like the Data Retrieval Agent built by Kensho, and then standardizing on Google Cloud. If you operate in financial services or other regulated data markets, the opportunity is to position as the partner that connects this AI‑ready foundation into client workflows and builds specialized agents on Gemini Enterprise

DXC Technology launched AdvisoryX, a consulting-led business designed to help enterprises move from AI pilots to scaled, production outcomes, backed by new global research on the “AI execution gap.” The study shows that while most leaders call AI a board-level priority, many still lack clear business cases and operating models. This often leads to stalled projects or fragmented experiments.

According to this new study released by DXC, leaders expect AI to meaningfully change how work gets done and how decisions are made:

AdvisoryX helps by connecting quick operational wins with a clear long-term strategy.

This is yet another proof point that parts of the market are stuck between AI ambition and execution reality. If you sell into large enterprises, expect more demand for partners who can define the business case, clean the data, and build a proper operating model. The study gives you useful language for customers and boards.

Lemongrass completed a strategic partnership with the SAP PartnerEdge Build Program for its Clean Core AI Accelerator, designed to help enterprises modernize SAP estates and adopt AI while preserving a clean core.

This is a helpful reminder that in the SAP ecosystem, AI adoption depends on clean data, upgraded platforms, and certified partners.

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*Data shared by DXC in a new global study conducted in August 2025 which included 2,496 participants who serve in technology and business leadership positions in global companies across 23 countries.

Disclaimer: This post is for information only and does not constitute investment advice or a recommendation to buy or sell any security. Views are my own and I’m not affiliated with any companies mentioned.