This story was originally published on CIO Dive. To receive daily news and insights, subscribe to our free daily CIO Dive newsletter. Dive Brief:  Accenture is deepening relationships with Microsoft and Databricks, two long-time technology partners, to ease AI adoption for enterprises. A day before its Q2 2026 earnings, Accenture announced plans to launch a forward deployed engineering practice with Microsoft. Separately, it’s launching the Accenture Databricks Business Group to build AI agent-ready datab ...

Summary of TMT Conference Private Company Takeaways - March 2026 Industry Overview - **Industry Focus**: Software and AI in North America - **Key Themes**: Evolution of AI from co-pilots to agents, platform expansion, competitive moats centered around proprietary data and infrastructure, and enterprise adoption of AI technologies [1][3][4][5][11][12] Core Insights 1. **AI Evolution**: AI is transitioning from being an assistant to an agent, with companies like OpenAI and Databricks leading the charge in automating workflows and enhancing productivity [3][11] 2. **Platform Expansion**: Companies are broadening their offerings into full platforms rather than remaining narrowly defined, as seen with Ramp and Airwallex [4][11] 3. **Competitive Moats**: The focus is shifting towards proprietary data, infrastructure, and governance as key competitive advantages, rather than just model quality [5][10] 4. **Enterprise Adoption**: AI is being adopted at an enterprise level, moving beyond experimentation to integrated solutions across various workflows [11][12] 5. **Growth Strategies**: Companies are focusing on global expansion, vertical penetration, and efficiency, with an emphasis on profitable growth while investing in AI [12] Company-Specific Insights OpenAI - **Revenue**: $25 billion ARR, with significant user growth in Codex (2 million users, 25% weekly growth) [21] - **Strategic Partnerships**: Collaborations with NVIDIA, Amazon, and SoftBank to enhance AI capabilities [21] - **Product Focus**: Emphasis on coworking automation and AI for scientific advancements [21] Databricks - **Revenue**: $5.4 billion ARR, with AI revenue exceeding $1.4 billion [27] - **Platform Strategy**: Positioning as a leading platform for AI with a focus on analytical capabilities and governance [27] - **Product Innovations**: Launching new products tailored for AI agents, including Lakebase [27] Canva - **User Base**: Over 260 million monthly active users, with significant enterprise growth [29][33] - **AI Integration**: Canva AI has been utilized 23 billion times, indicating strong adoption [33] - **Investment Focus**: Prioritizing AI, international expansion, and enterprise growth [33] Ramp - **Revenue**: Over $1 billion in annualized gross revenue [34] - **Market Position**: Significant growth in financial operations, with a focus on integrated solutions [38] - **AI Utilization**: Extensive use of AI agents to automate financial tasks [38] ElevenLabs - **Revenue**: $330 million ARR, with a 175% YoY increase [43] - **Product Complexity**: Focus on natural-sounding speech synthesis and voice AI technology [39] - **Market Applications**: Diverse use cases across industries, including government and education [43] Kraken - **Revenue**: $500 million ARR, with a focus on digital transformation for utilities [47] - **Customer Base**: Managing over 70 million customer accounts [45] - **Growth Strategy**: Targeting new markets in the US and Japan [47] Harvey - **Customer Base**: Over 1,000 clients, including major law firms [52] - **Product Offerings**: AI tools for legal workflows, emphasizing efficiency and integration [52] - **International Presence**: Significant international customer base, requiring localization [52] Airwallex - **Revenue**: $1 billion ARR, with 90% YoY growth [56] - **Business Model**: Combining capabilities of multiple financial platforms into one [56] - **Market Focus**: Targeting businesses with global operations [56] Cohesity - **Revenue**: $1.5 billion ARR, focusing on data security and resilience [64] - **Acquisition Strategy**: Successfully integrated Veritas, expanding customer base significantly [66] - **AI Strategy**: Positioning as a data lake for AI, focusing on backup data [66] Abnormal AI - **Revenue**: $200 million, with over 100% YoY growth [68] - **Product Focus**: Human behavior security platform leveraging machine learning [67] - **Market Reach**: Trusted by over 3,200 organizations, including 25% of the Fortune 500 [67] Additional Insights - **Investment Trends**: Companies are increasingly focusing on AI investments while maintaining margin discipline [12] - **Market Dynamics**: The competitive landscape is evolving with a focus on integrated solutions and customer-centric approaches [11][12] This summary encapsulates the key takeaways from the TMT Conference, highlighting the evolving landscape of AI and software companies, their growth strategies, and the competitive dynamics shaping the industry.

Accenture (NYSE: ACN) and Databricks have deepened their collaboration to help businesses worldwide harness enterprise data more effectively and rapidly expand the use of sophisticated AI applications and intelligent agents. The two companies announced the creation of the Accenture Databricks Business Group on March 17, 2026, a dedicated initiative backed by over 25,000 professionals trained extensively on Databricks technologies—including what is described as the industry’s largest pool of certified profes ...

Core Insights - Accenture and Databricks have launched the Accenture Databricks Business Group to assist organizations in implementing Databricks' data and AI platform [1] - The initiative aims to address challenges in scaling AI due to fragmented data systems and legacy infrastructure [2] Group 1: Partnership and Objectives - The partnership focuses on centralizing data governance and facilitating the transition of AI from pilot stages to operational use [2] - The new business group will be staffed by over 25,000 professionals trained in Databricks technology [4] Group 2: Industry Applications - Clients in various sectors, such as US retailer Albertsons Companies and chemical firm BASF, are utilizing the services for pricing intelligence and digital assistants [3] - The initiative aims to deploy solutions like Lakebase, Genie, and Agent Bricks across industries including financial services, retail, and telecommunications [5] Group 3: Educational Initiatives - A university program in India targets final-year engineering students to join Accenture after graduation, linked to Databricks' commitment to invest $250 million in India over three years [6]

Core Insights - Databricks plans to raise over $4 billion in a Series L funding round, valuing the company at $134 billion [1] - The company achieved a revenue run-rate exceeding $4.8 billion in Q3, with a year-on-year growth of over 55% [1] - Databricks has generated positive free cash flow over the past 12 months since December 2024 [1] Funding Details - The Series L investment is led by Insight Partners, Fidelity Management & Research Company, and JP Morgan Asset Management, with additional investors including Andreessen Horowitz and BlackRock [2] - The funding will support product development in three strategic areas: Lakebase, Databricks Apps, and Agent Bricks [2] Product Development Focus - The funding aims to assist customers in developing AI applications and agent-based tools using proprietary data, positioning Lakebase as the system of record [3] - Databricks Apps allows organizations to quickly and securely build and deploy data and AI applications, while Agent Bricks simplifies the creation and scaling of high-quality agents [4] - Lakebase is a serverless PostgreSQL database designed to support AI-era workloads [4] Market Position and Growth - Databricks co-founder and CEO Ali Ghodsi emphasized the rapid transformation in how enterprises build intelligent applications, driven by generative AI and new coding paradigms [5] - Lakebase has attracted thousands of customers in its first six months, generating revenue growth at double the pace of the data warehousing product [5] - The Data Warehousing product reached a revenue run-rate of over $1 billion in less than four years, while AI products also achieved a revenue run-rate of over $1 billion [6] - Databricks maintains a net retention rate above 140%, with over 700 customers generating an annual revenue run-rate exceeding $1 million [6]

Core Insights - Databricks has successfully raised over $4 billion in a Series L funding round, achieving a valuation of $134 billion, which is a 34% increase from its previous valuation of $100 billion just three months ago [1] - The company is focusing on developing products that cater to the AI revolution, including a database for AI agents, an AI agent platform, and applications for building and deploying data and AI solutions [2] Funding and Valuation - This funding round marks Databricks' third major venture fundraising effort within a year, reflecting strong investor confidence in the company's ability to leverage data for AI applications [4] - The company was valued at $60 billion around the same time last year, indicating significant growth in investor belief regarding its potential [4] Revenue Growth - Databricks reported a run-rate revenue exceeding $4.8 billion, which represents a 55% increase from the previous year, with over $1 billion of that revenue coming from AI products [4] Product Development - The company is heavily investing in its AI agent database, Lakebase, which is based on the open-source Postgres database, and aims to support corporate developers in their projects [3] - Databricks' AI agent platform, Agent Bricks, is designed to assist businesses in building and deploying AI agents that utilize their data [3] Strategic Partnerships - Databricks has secured significant deals worth hundreds of millions with AI labs such as Anthropic and OpenAI to integrate their models into its enterprise products [3] Job Creation and Expansion - The new funding will be utilized to create thousands of new jobs across Asia, Europe, and Latin America, as well as to recruit more AI researchers [6] Investor Participation - The funding round was led by notable firms including Insight Partners, Fidelity, and J.P. Morgan Asset Management, with participation from several other prominent investors [7]

Core Insights - Databricks is integrating OpenAI's models, including GPT-5, into its data platform and AI product, Agent Bricks, through a $100 million multi-year deal aimed at attracting enterprise customers [1][5] - The partnership emphasizes the growing demand for generative AI tools that can securely access corporate data [1] Company Developments - Agent Bricks allows organizations to create AI applications and agents using various AI models, with OpenAI's latest models now available via SQL or API, positioning GPT-5 as a flagship offering [2] - Databricks previously incorporated OpenAI's open-weight models, gpt-oss 20B and gpt-oss 120B, enhancing the platform's capabilities [3] Strategic Implications - OpenAI's COO highlighted that the partnership facilitates the deployment and scaling of AI agents within secure enterprise environments, potentially leading to significant business impacts [4] - Databricks is committed to a minimum payment of $100 million to OpenAI, regardless of the revenue generated from the models, indicating a strategic bet on the adoption of these AI tools by enterprise customers [5][6] Market Context - The deal mirrors a previous agreement Databricks made with Anthropic, which also set a revenue target of $100 million over five years, reflecting a trend in the industry towards securing partnerships with AI firms [7] - Databricks has reported strong demand from clients, including Mastercard, for direct access to OpenAI's models, suggesting a robust market interest in AI integration [7]

Core Insights - Databricks has partnered with OpenAI to integrate AI models into its platforms for enterprise customers, enhancing its cloud platform and flagship product, Agent Bricks [1][2] - The partnership is projected to generate $100 million in revenue, positioning Databricks favorably against competitors like Snowflake [2][3] - The deal will provide access to GPT-5 for over 20,000 enterprise customers, addressing the growing demand for AI applications tailored to specific business needs [3] Company Developments - Databricks is enhancing its capabilities by integrating OpenAI's models, which will improve the development and scaling of AI applications for enterprise clients [1][2] - The company recently secured a $1 billion funding round, achieving a valuation of $100 billion, making it one of the most valuable private companies globally [4] Market Position - The partnership with OpenAI allows Databricks to gain a competitive edge in the enterprise AI sector, particularly over rivals still developing their AI capabilities [2][3] - OpenAI is expanding its enterprise business beyond Microsoft Azure, aiming for broader adoption of its AI tools among corporate customers [2]

Core Insights - Databricks has achieved a valuation of $100 billion, making it the fourth-largest AI unicorn globally, following OpenAI, ByteDance, and xAI [1] - The company has an annual revenue of $3.7 billion and serves over 15,000 customers, with 60% of Fortune 500 companies utilizing its products [1][12] - The company's growth is attributed to its innovative "lakehouse" architecture, which integrates data lakes and data warehouses, enhancing data management for AI applications [4][6] Company Background - Databricks was founded by a team of PhD graduates from the University of California, Berkeley, including co-founder Reynold Xin [2][3] - The company initially struggled with monetization, leading to the appointment of Ali Ghodsi as CEO, who transformed the company's management approach [3][11] Business Strategy - Databricks is heavily investing in AI, planning to spend $1.5 billion from 2022 to 2025 to enhance its AI capabilities [10] - The company has made significant acquisitions, including spending $1.3 billion on MosaicML and $1 billion on Neon, to bolster its AI development services [11][12] - Databricks has introduced new services like Agent Bricks and Lakebase, aimed at simplifying AI model creation and enhancing database performance [12] Financial Performance - The company's revenue from generative AI products has increased by 300% year-over-year as of November 2024 [12] - Databricks expects its annual revenue to reach $3.7 billion by July 2024, reflecting a 50% year-over-year growth [12] Market Position and Competition - Databricks is facing intense competition from data giants like Snowflake and Oracle, as well as cloud service providers such as Microsoft, Google, and AWS [13][15] - Despite its strong revenue growth, Databricks' market position is still slightly behind Google and Snowflake in terms of scale [15] - The company is under pressure to demonstrate the value of its new Agent services to investors, as these offerings are still in early development stages [15]

Core Insights - Databricks has achieved a valuation of over $100 billion following a Series K investment, positioning itself as a significant player in the AI and enterprise software market [1][2] - The company plans to utilize its new capital to accelerate its AI strategy, particularly through the launch of Agent Bricks, which targets the emerging agentic AI market [3] - Databricks is seen as a competitor to Palantir, which has a market cap of approximately $340 billion, indicating a substantial valuation gap between the two companies [2][12] Company Overview - Databricks offers a Lakehouse platform that consolidates fragmented and siloed data from various enterprise tools, enabling organizations to derive actionable insights more efficiently [5][6] - The platform is already utilized by over 15,000 businesses, including more than 60% of the Fortune 500 [6] Agentic AI - Agentic AI represents a significant advancement over traditional large language models, allowing AI agents to take proactive actions rather than merely responding to prompts [9][11] - These AI agents can autonomously analyze problems, formulate execution plans, and carry them out with minimal oversight, potentially transforming operational efficiency for large corporations [10][11] Financial Comparison - Databricks is reportedly generating an annual recurring revenue (ARR) run rate of approximately $3.7 billion, while Palantir's 2025 financial guidance suggests a midpoint of $4.1 billion in annual sales [12][13] - The valuation gap between the two companies is attributed to Palantir's consistent profitability and established platforms, which serve as AI backbones for large enterprises and government agencies [13] Strategic Positioning - Databricks aims to close the valuation gap by evolving into a comprehensive operating system that unifies enterprise data architectures, with a strong focus on agentic AI [14] - The company is currently accessible to accredited investors or through secondary offerings, with potential for an initial public offering (IPO) in the future, possibly at a lower valuation compared to Palantir [15]