Trends Shaping Tech Ecosystems

Since 2012, the Machine Learning, AI & Data (MAD) ecosystem is captured by FirstMark's Landscape reports which show the rapidly evolving ecosystem of AI, data, and analytics. See for an interactive, reader-friendly, and accessible format of the 2024 MAD Landscape: https://mad.firstmark.com/ PDF (below): https://lnkd.in/gwFJfzSe * * * The Landscape's 2024 edition, published in March 2024, now features 2,011 companies, up from 1,416 in 2023 and just 139 in 2012. According to Matt Turck's blog post, providing an overview of the trends, growth is fueled by 2 massive cycles: - The "Data Infrastructure" wave - a decade-long cycle which emphasized data storage, processing, and analytics, from Big Data to the Modern Data Stack. Despite expectations for consolidation in this space, it hasn’t occurred yet, resulting in a large number of companies continuing to operate independently. - The second wave is the "ML/AI cycle", which gained momentum with the rise of Generative AI. Since this cycle is still in its early stages, the MAD Landscape included emerging startups. These 2 waves are deeply interconnected, with the MAD Landscape emphasizing the symbiotic relationship between data infrastructure, analytics/BI and ML/AI, and applications. * * * In the area of AI Governance, Security, and Risk, AI-specific startups and tools are on the rise: - “AI Observability” include startups that help test, evaluate and monitor LLM applications  - “AI Developer Platforms” is close to MLOps, but recognizes the wave of platforms that are wholly focused on AI application development, in particular around LLM training, deployment and inference - “AI Safety & Security” includes companies addressing concerns innate to LLMs, from hallucination to ethics, regulatory compliance, etc * * * 24 key themes shaping the industry are identified: - Distinct pipelines and tools for structured and unstructured data - Maturation and potential consolidation of the Modern Data Stack - Data Quality and Observability: Growing importance of tools that ensure data accuracy and reliability - Increasing focus on data governance frameworks and privacy regulations - Rise of technologies enabling real-time data analytics and decision-making - Data Integration and Interoperability - Data Democratization: Broader access to data and analytics tools - Recognizing the critical contributions of Data Engineers - Impact of Generative AI - Hybrid Future: Coexistence and integration of LLMs and SLMs - Relevance of traditional AI approaches in the era of GenAI - Strategies of orgs building on top of existing AI models vs. developing comprehensive solutions - AI Agents and Edge AI - AI Safety and Ethics - AI Regulation and Policy implications for businesses - Demand for AI Talent and Education - AI in Healthcare - AI in Finance - AI in Retail and E-commerce - AI in Manufacturing - AI in Education - AI in Entertainment and Media - AI and Climate Change - The Future of Work

This year, the State of Data and AI Engineering report has been marked by consolidation, innovation and strategic shifts across the data infrastructure landscape. I identified 5 key trends that are defining a data engineering ecosystem that is increasingly AI-driven, performance-focused and strategically realigned. Here's a sneak peek at what the report covers: - The Diminishing MLOps Landscape: As the standalone MLOps space is rapidly consolidating, capabilities are being absorbed into broader platforms, signaling a shift toward unified, end-to-end AI systems. - LLM Accuracy, Monitoring & Performance is Blooming: Following 2024's shift toward LLM accuracy monitoring, ensuring the reliability of generative AI models has moved from "nice-to-have" to business-critical. - AWS Glue and Catalog Vendor Lock-in: While Snowflake just announced read/write support for federated Iceberg REST catalogs, finally loosening its catalog grip, AWS Glue is already offering full read/write federation, and is therefore the neutral catalog of choice for teams avoiding vendor lock-in. - Storage Providers Are Prioritizing Performance: in line with the growing demand for low-latency storage, we see a broader trend in which cloud providers are racing to meet the storage needs of AI and real-time analytics workloads. - BigQuery's Ascent in the Data Warehouse Wars: with 5x the number of customers of both Snowflake and Databricks combined, BigQuery is solidifying its role as a cornerstone of Google Cloud’s data and AI stack. These trends highlight how data engineering is evolving at an unprecedented pace to meet the demands of a rapidly changing technological landscape. Want to dive deeper into these critical insights and understand their implications for your data strategy? Read the full report here: https://lnkd.in/dPCYrgg6 #DataEngineering #AI #DataStrategy #TechTrends #DataInfrastructure #GenerativeAI #DataQuality #MLOps

The intelligence sector is experiencing rapid consolidation with transaction multiples diverging based on technology integration. Data-first platforms command 15-20x revenue multiples, while traditional advisory firms trade at 3-4x. Private equity firms are driving consolidation through platform investments, typically acquiring technology-enabled companies at 8-12x EBITDA followed by tuck-in acquisitions at 5-7x. Since 2020, dozens of significant transactions have occurred with median deal size growing from $120M to $275M. Prominent PE-backed roll-ups abound. The sector is bifurcating between premium assets with AI capabilities (commanding 40% valuation premiums) and commodity intelligence providers facing margin pressure. Strategic buyers are entering the space, paying up to 15x forward revenue for specialized capabilities. Recurring revenue percentage directly correlates with multiple expansion, with companies transitioning from services to subscription models experiencing valuation uplift from 3-5x to 8-12x revenue. Buy-side investors increasingly target companies with proprietary data assets, API-first architectures, and 80%+ gross margins. Industry-specific intelligence solutions command 30% price premiums over general offerings. Overall sector growth continues at 16-20% annually, outpacing broader cybersecurity at 12%. Future consolidation will likely reduce significant players over five years. Valuation premiums will be linked to unique data collection methodologies and technology-enabled delivery models. The emerging trend of intelligence "ecosystems" is noteworthy, as platform companies create marketplaces for specialized providers, enabling an additional valuation premium for ecosystem participants versus standalone counterparts.

Something interesting is happening in startup world. I'm noticing founders more interested in learning about: • Marketing strategy • Content creation • Creator partnerships • Community building Than: • Product development • Tech infrastructure • Feature optimization Five years ago this would've been considered crazy, especially in SF. Today? It might actually be the smartest move. Think about it... AI can help you copy any product feature. Tech is becoming less of a moat every day. Infrastructure is getting easier and easier to replicate. But you know what's getting harder to copy? • Real community • Owned distribution • Brand trust • Founder+Audience empathy I'm watching VCs quietly shift too... Instead of asking "How sticky is the product?" Now they're asking "How are you thinking about distribution?" The startups winning right now? They're not winning on tech. They're winning on brand & reach. Because in 2025, the best product doesn't win. The best distribution does. #startups #entrepreneurship #business

CES 2025: Insights for Tech Leaders Navigating Innovation CES 2025 is proving to be a masterclass in the art of disruption. From generative AI redefining workflows to sustainable tech becoming the new industry standard, this year’s announcements aren’t just exciting—they’re transformational. Here are the highlights every tech executive should care about: 🤖 Generative AI Takes Charge: No longer a buzzword, it’s now a business-critical tool reshaping customer interactions and operational efficiency. 🌍 Sustainability Meets Innovation: Energy-efficient devices and eco-conscious designs are driving market leadership—because customers and investors demand it. 🚗 Mobility Reimagined: AI-powered EVs and autonomous platforms are turning transportation into a data-driven ecosystem. 💡 Health Tech and Wearables: From hydration tracking to stress management, health-focused tech is evolving into proactive wellness ecosystems. The takeaway? The future is no longer something we prepare for—it’s something we create. These trends demand bold strategies and forward-thinking leadership to stay ahead in the race to innovate. What CES 2025 trends resonate most with your strategy? Let’s connect and discuss how we can transform insights into action. 📖 Read the full breakdown: https://lnkd.in/gF9TwZNb #CES2025 #TechLeadership #InnovationStrategy #SustainabilityInTech #AIIntegration

Corporate Venturing in the 🇺🇸 Isn’t Just About Silicon Valley. According to the new #CorporateStartupActivityIndex2025 by StartupBlink, the U.S. remains the global leader in corporate startup engagement. 135 U.S. based corporations are listed, more than 5 times the number from the next highest country, Japan. That’s not surprising. But here’s what is: The most exciting corporate venturing is not always happening where you think. Yes, you’ll see Salesforce, Intel, and Google at the top of the rankings. But beneath the surface, there’s a shift: Innovation is getting geographically distributed. Look at some of the standouts from beyond the usual suspects: #Illinois: Caterpillar is engaging with sustainability startups, embedding innovation into industrial supply chains. #NorthCarolina: LabCorp is partnering with healthtech founders to improve diagnostics and patient pathways. #Massachusetts: HubSpot and Thermo Fisher are shaping the next wave of B2B SaaS and biotech through venture partnerships. These companies are quietly doing what many high profile programs can’t: Integrating startups into core business lines Co-developing solutions with measurable impact And building startup ready infrastructure outside the coastal tech bubbles. If you’re a startup founder Don’t just chase the usual names. Chase corporations that have clarity, commitment, and a structure that supports growth. If you’re serious about taking action to improve these connections, I want to help. 👉 Fill out this short form and let’s explore how we can work together: https://bit.ly/46sEiNR #corporateventuring #startups #openinnovation #ecosystems #innovationstrategy #impact #startupcollaboration #supplychaininnovation #healthtech YES, my photo is old ;) My hair looks different hehe

The Canalys Channels Ecosystem Landscape offers an in-depth look at the technologies shaping competitive advantage for channel and partnership leaders. With 261 companies driving US$7.46 billion in revenue in 2024, this ecosystem is rapidly evolving towards a projected US$13.48 billion by 2028, highlighting the crucial role of automation and data-driven decision-making in partnership success. For 8 years, this unique “tech stack” research brings focus to the underlying technologies that will drive competitive advantage for channel and partnership leaders in the decade of the ecosystem. The hundreds of software companies represented in the landscape are providing automation and advanced digital capabilities to help companies design, develop, execute and manage a broad channel partner and alliance ecosystem. There are increasing demands on channel leaders to find, recruit, onboard, develop, incentivize, co-sell, co-market, co-innovate, measure, manage and report on partner value at scale. Automation of partner-related workflows, deeper integrations and data-driven decision-making create measurable competitive advantages (through partnerships) and are quickly becoming table stakes in the industry.

Hello, Network! 🌐 Today, I had an enlightening conversation with a VC that could have major implications for tech startups and established foundational industries like the energy sector. 🎯 The Insight: Corporates in foundational sectors are actively looking to invest in venture funds. The goal? To identify groundbreaking technologies and trends that will enable them to scale their operations without increasing their workforce. 🔥 What's Hot: Technologies that optimize the value chain, like user-friendly AI solutions and vertical SaaS platforms, will be on the radar of these giants to adopt more technology. 👥 The Impact: This approach could set a new precedent in how foundational industries seek to innovate and grow, providing a massive opportunity for tech startups and entrepreneurs to contribute disruptive solutions. What are your thoughts on this trend? How will it shape the future of tech investing? Drop your thoughts below! 👇 #venturecapital #technology #AI #SaaS #scaling #investmenttrends

📈 Due to AI, We See A 𝗥𝗶𝘀𝗲 𝗼𝗳 𝗦𝗼𝗹𝗼 𝗙𝗼𝘂𝗻𝗱𝗲𝗿𝘀 that is reshaping the startup landscape! 🚀 🔹 Solo founders increased from just 17% in 2017 to an impressive 36% in 2024. 🔹 However, only 16%-19% of VC-backed startups are solo-led, highlighting investors' preference for founding teams. (Thanks to Carta research for data) So, what's driving this shift? 💡 🔑 𝗟𝗼𝘄𝗲𝗿 𝗕𝗮𝗿𝗿𝗶𝗲𝗿𝘀 𝘁𝗼 𝗘𝗻𝘁𝗿𝘆: Starting a company is now easier than ever, encouraging more individuals to take the entrepreneurial leap solo. 💸 𝗕𝗼𝗼𝘁𝘀𝘁𝗿𝗮𝗽𝗽𝗶𝗻𝗴 𝗚𝗿𝗼𝘄𝘁𝗵: Many solo founders opt out of traditional VC funding, leveraging bootstrapping techniques combined with powerful AI tools for rapid growth. 🤖 𝗔𝗜 𝗖𝗵𝗮𝗻𝗴𝗶𝗻𝗴 𝘁𝗵𝗲 𝗚𝗮𝗺𝗲: AI significantly reduces startup costs and complexity, making it possible to scale quickly without large teams or heavy initial investments. 💬 Why does this matter? We're entering a new era where micro-startups could become the norm. This shift empowers innovation at an individual level and democratizes entrepreneurship. Whether you're an investor, a founder, or thinking about your next move, understanding this trend is crucial to staying ahead. ✨ 𝗜𝗺𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗬𝗢𝗨: Investors might need to reconsider their biases towards founding teams. Solo founders must leverage AI and strategic hiring to stay competitive. The broader ecosystem should prepare for a more fragmented yet dynamic startup environment. What do you think—is this the future of startups? I'd love to hear your insights! 👇