By Moshe Zalcberg
In an industry where three companies control 92 pecent of the market, disruption seems nearly impossible. Yet at the recent Design Automation Conference (DAC), a new wave of AI-powered startups presented their bold ambitions to crack the Electronic Design Automation (EDA) industry’s iron grip.
The question isn’t whether disruption will come. It is whether these newcomers have the right strategy to succeed where others have failed.
One of the key presentations every year at DAC is “A View from Wall Street,” when senior industry analyst Jay Vleeschhouwer from Griffin Securities reviews the “State of EDA.” Among the data and statistics presented, Jay revealed that a staggering 92 percent of all EDA spending flows to just three companies: Synopsys (including Ansys, which Synopsys bought last week), Cadence, and Siemens EDA. This level of concentration has increased in recent years, representing decades of market consolidation through acquisitions and the creation of comprehensive tool suites that customers find difficult to abandon.
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A View from Wall Street” by Jay Vleeschhouwer from Griffin Securities
The EDA industry’s three-company dominance places it among the most concentrated markets globally. Few industries exhibit such extreme characteristics: the insulin market shows similar patterns with Eli Lilly, Novo Nordisk, and Sanofi controlling over 90 percent globally; U.S. wireless carriers demonstrate even more extreme concentration with T-Mobile, Verizon, and AT&T commanding 99.1 percent market share.
While AI inference hardware presents an interesting contrast where Nvidia alone controls an estimated 70 percent to 95 percent of the market. (Not even the public cloud business is so concentrated: the “big-three” there command “only” 60 percent of the market). These comparisons highlight that while extreme concentration is rare, it tends to occur in industries with high technical barriers, significant switching costs, and mission-critical applications, all characteristics that define the EDA landscape.
AI creates unprecedented opportunities
Despite this concentration, AI is creating unprecedented opportunities to challenge the established order. An interesting luncheon panel sponsored by Accelera at DAC focused on the topic: Can AI Cut Costs in Electronic Design & Verification While Accelerating Time-To-Market?
The panel touched on different topics related to the introduction of AI tools, such as the availability of training data, the possibility of sharing data among different organizations, and how to convince teams to adopt AI. When the moderator invited questions from the audience, I asked to return to the original theme of the panel: “Two years from now, at what rate will we be cutting costs or accelerating design and verification? Would it be 10 percent? 50 percent? 90 percent?”
The responses were telling. Dr. Erik Berg from Microsoft posited that in two years, he believes we’ll be able to cut 50 percent of the total effort. Dr. Monica Farkash from AMD observed that we don’t need to wait two years, as much of this capability is available today. Finally, Chuck Alpert from Cadence said that instead of cutting costs and time by 50 percent, he expects customers to do “twice as much” more verification, bigger designs, and so on.
While valid on its own merit, this answer also aligns with EDA vendors’ interests: that users continue to spend the same or more while achieving better results.
Accelera-sponsored luncheon at DAC
In fact, the session on the “Future of Verification,” led by Veriest’s vice president of frontend engineering Dusica Glisic, featured experts from AMD, ARM, Intel, and Marvell, who provided more details about real-life use cases of how AI is already benefiting verification practices. They discussed not just how this impacts development flows but also the actual roles and training of design and verification teams, from senior to junior engineers.
Veriest session on the “Future of Verification”
The design and verification focus: Why these domains?
It’s not coincidental that the overwhelming focus of AI-powered solutions is on design and verification.
Design and verification are fundamentally language-based domains. RTL code, SystemVerilog, assertions, and constraints are all textual representations that large language models can naturally understand and manipulate. This linguistic foundation gives AI a significant advantage over traditional rule-based approaches, as modern language models excel at understanding context, patterns, and generating coherent code structures. The similarity between natural language programming and hardware description languages creates a natural bridge for AI applications.
From a practical standpoint, verification has become the primary bottleneck in chip development, often consuming 60 percent to 70 percent of design time. As chip complexity has exploded, traditional verification approaches struggle to keep pace. AI’s pattern recognition capabilities offer genuine potential for breakthrough improvements in test generation, bug detection, and coverage analysis.
The data-rich nature of these domains also provides substantial training opportunities. Simulation results, timing reports, coverage databases, and design histories generate vast amounts of structured data that can train AI models effectively. This data availability, combined with the quantifiable nature of improvements (faster simulation, better coverage, reduced power consumption), makes design and verification attractive targets for AI-powered solutions.
The new wave: Unprecedented scale of disruption
The scale of current disruption attempts is unprecedented, both within the big EDA players and among a host of new startups active in this field. At Veriest, we’ve been tracking this market segment with keen interest, evaluating the value proposition of different offerings and applying them to various use cases to measure their impact and benefit.
As part of this interest, we’ve compiled a market landscape map of such startups. This is not a complete map, and we’ll be adding additional companies as we learn about them, but you can still see the concentration around verification I’ve mentioned above:
To promote debate about this new and exciting trend, we organized another DAC session on “AI-Enabled EDA for Chip Design,” curated by Veriest’s Predrag Nikolic, which showcased seven of such innovative startups: ChipStack, Silimate, Rise-DA, ChipAgents, VerifAI, Bronco AI, and Verifaix. The audience in the packed room was able to get a broad perspective of the different technologies and use cases in one single session.
It was also interesting to note that around half of the founders of such startups are EDA or chip design veterans who are learning how to leverage AI in their practice, while the other half are AI specialists who chose the EDA market to apply their expertise.
Veriest session on the “AI-Enabled EDA for Chip Design”
A novelty: VCs discover the EDA industry
Indeed, there is a plethora of new EDA startups, and customers are noticing them, talking to them, evaluating their tools, and often adding them to their design flows. But there’s another group that has been closely following this new trend: venture capitalist investors.
In the past, meeting a VC at DAC would be rare. As a VC, why would you bother spending time in an industry so concentrated, where customers are very conservative and where your only exit strategy is to look for an M&A transaction with one of the three big players?
But it turns out that many VCs are taking notice of this emergent market segment. According to PitchBook and other public data, VC firms such as Khosla Ventures, First Spark Ventures, Celesta Capital, Clear Ventures, Y Combinator, 468 Capital, Koro Capital, Cerberus, and AHN Ventures have invested in this field and many other major VCs are active in stealth mode.
In this context, I took special interest in initiating, organizing, and moderating a panel on the investment thesis that these VCs are considering. The panel, named “The Renaissance of EDA Start-ups” featured VCs Kanu Gulati from Khosla Ventures and Brian Schechter from Primary Venture Partners alongside Erfan Rostami from Voltai providing the entrepreneur’s perspective, and Vinod Kariat from Cadence — who joined after his startup was acquired — who offered insights into how established companies view newcomers.
“The Renaissance of EDA start-ups” panel
Breaking through: Strategic approaches for success
The panel outlined the special challenges that these startups need to face: starting in a very concentrated market, conservative customers, the need to validate tools due to the high cost of failure, and the effort required to integrate seamlessly with existing flows, to name a few.
Despite these challenges, several strategies offer paths to market penetration. These approaches were actively discussed by the panelists.
- Choose the right customers to engage: Target design teams that have fewer legacy constraints and are more willing to experiment with new tools. These customers can provide crucial early validation and case studies that larger companies will eventually notice.
- Point solution strategy: Despite the fact that entrepreneurs often tell VCs they will be “the next Cadence/Synopsys/Mentor,” it’s wiser to focus on solving specific, painful problems where AI provides clear advantages, rather than attempting to replace entire flows.
- Unique value: Don’t take a problem that is mostly solved, offering a slightly better solution. And don’t focus just on a new tool.
Focus on tasks that don’t have good solutions and add value by solving them end-to-end. - Cloud-first deployment: Leverage cloud delivery to reduce barriers to trial and adoption. Usage-based pricing models can make it easier for customers to experiment without large upfront investments, following the pattern of successful software disruptions.
- New business models: Just like “AirBNB”, the innovation may come not just from the technology, but how the business is structured, unlocking new value propositions.
The path forward
The current wave of AI-powered EDA startups represents the most significant disruption attempt the industry has seen in years. The combination of genuine AI breakthroughs, growing chip complexity, and expanding market size creates real opportunities for success. The packed rooms at DAC sessions and the urgency expressed by industry leaders suggest that this disruption wave has substance beyond typical hype cycles.
The key insight from industry veterans is that success won’t come from directly replacing the big three players, but from creating compelling point solutions that eventually force these companies to acquire or partner with the startups. History shows that the EDA industry’s concentration has been built through acquisition, and the most successful strategy for newcomers may be to position themselves as attractive acquisition targets while building sustainable businesses.
In a market growing at 9 percent annually and projected to reach $27 billion by 2031, there’s room for both evolution and revolution. The AI-powered startups showcased at DAC represent the vanguard of this transformation, armed with better tools, clearer strategies, and a deeper understanding of customer needs than previous disruption attempts. Their success will depend on execution, timing, and the ability to build trust in an industry where failure is measured in hundreds of millions of dollars.
The disruption wave is real, but success will require more than just superior technology. It will demand strategic thinking, customer focus, and the patience to play the long game in an industry that rewards persistence over promises.
Moshe Zalcberg is CEO of Veriest Solutions, a leading ASIC services company, as well as a Partner at Silicon Catalyst, and as such, he is exposed to a range of semiconductor projects and a variety of design & verification approaches. He has more than 20 years of experience in the semiconductor and design automation industries, having spent over 12 years of his career at Cadence Design Systems, in roles that include General Manager, Israel and European head of Professional Services. Moshe is an electrical engineering graduate of the Technion Israel Institute of Technology and holds an MSc in Electronics and an MBA, both from Tel Aviv University.
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