Eran Zinman on Monday.com’s AI Pivot, Pricing and Software Markets

Monday.com co-founder and CEO Eran Zinman joins Harry Stebbings to discuss AI, software valuations and the company’s response to a falling share price. Zinman has a substantial personal stake in Monday.com and Stebbings says he holds its shares; both have financial interests relevant to their discussion. Company figures are their accounts at the time, not current quotations or independently verified financial statements.

Zinman says the period has been emotionally difficult and distinguishes company operations from a rapid change in market sentiment toward software. He acknowledges that investor concerns contain some truth, while arguing that the businesses and their share prices are not the same thing. This is his interpretation of the market, not proof that any stock is mispriced.

He lists several possible threats: customers building their own applications with AI, model providers capturing application value, and existing software becoming a database behind agents. Stebbings asks first about a journalist recreating a Monday-like interface. Zinman says the demonstration was impressive but argues that an interface is different from a secure, maintained system used across an organization.

Stebbings presses on small businesses and individual users who might build simpler replacements. Zinman believes the effect will be limited because maintaining and adapting software requires work, while businesses have their own core operations to run. This is a prediction by the CEO of a software vendor and does not establish the magnitude of future substitution.

Stebbings argues that specialized legal companies may have accumulated data that a quick prototype lacks. Zinman disagrees about how much data is necessary for value and notes that Monday itself offers AI-assisted building. They do not test either claim, and neither a prototype nor a company valuation alone proves how difficult a full product is to replace.

On the possibility that OpenAI, Anthropic or Google capture enterprise applications, Zinman expects them to take some value but not the whole market. He compares AI infrastructure with cloud platforms that enabled other software businesses. He says enterprise deployment, sales and support require different capabilities; this is his competitive thesis rather than a guarantee about model providers’ strategies.

Zinman treats the possibility of existing products becoming systems of record as a more serious challenge. He argues that traditional software has often tracked work performed elsewhere, while AI could perform a larger portion of the work itself. His suggested 70%–80% share is a forward-looking illustration, not a measured result across occupations.

He says Monday must change its product rather than rely on being a database, and understands why investors are unsure which incumbents can adapt. He predicts the addressable market for software spending could eventually be 100 times larger. The interview provides no model or time frame supporting that estimate, and it is not a company revenue forecast.

Zinman gives an approximate example of a company spending much more on headcount than software, and speculates that AI could shift some future spending toward software. Stebbings points out that Monday’s analyst presentation showed headcount growth. Zinman says the more recent expectation was mid-teens growth and that the company is managing a transition; the figure is a plan, not a promise.

Stebbings asks why the company does not cut more aggressively. Zinman says management is discussing the issue but does not believe a dramatic headcount reduction alone would resolve investors’ concerns. In his account, shareholders want evidence that the business can capture demand and accelerate revenue, a result Monday has yet to demonstrate in this conversation.

Zinman describes internal AI use in sales and support. He says agents now handle the inbound qualification work previously done by a team of about 100 sales-development staff, while those employees moved to outbound work. This is a task and staffing description from the company, not evidence that 100 people were laid off or that all sales work was automated.

He says the inbound process used to take about 24 hours on average to respond and now takes about three minutes, with improved answer and conversion measures. Those metrics are his company-reported comparison; the interview does not provide a study, dates, denominators or a breakdown of all results. He says the sales solution was built internally.

For support, Zinman says Monday uses some outside technology as well as internal tools, which still require customization. He reports that engineers use AI coding tools and that output has increased, but says improving one step reveals other bottlenecks. These are operational observations rather than independently measured productivity gains.

Asked about 2030, he says the company then had about 3,000 employees and guesses the number may not grow substantially. He emphasizes that the company wants to pursue new revenue opportunities as well as efficiency. His headcount answer is a personal expectation, not a committed staffing target.

Zinman acknowledges that Monday initially added AI features without changing the product’s fundamental value. He describes an eventual shift from that “AI dust” toward rethinking onboarding, marketing, pricing and what the software actually does. His account is a company strategy and does not establish that the transition will succeed.

On pricing, he predicts a transition from seat-based charges toward a hybrid model and eventually consumption-based pricing. This is his view of a possible direction, not an announced schedule for all customers or proof that seat pricing will disappear across software. Stebbings highlights the difficulty of changing a model tied to customer headcount.

Zinman describes Monday’s proposed role as a horizontal workspace where people and agents coordinate, while specialist tools handle specific tasks. He imagines agents producing documents and tables for people to review. He acknowledges a long transition with humans involved and says fully autonomous work is uncertain.

Stebbings challenges whether model providers with strong brands and enterprise contracts could build the same thing. Zinman distinguishes an individual model license from a collaborative organizational workflow and argues that customers will need help configuring agents. His distinction is an interested assessment of competition, not proof that model providers cannot offer collaboration products.

The CEO says Monday is shifting its product toward agents, with boards and dashboards serving more of a background role. He calls it a major and risky change and expects more applications to be built on top of models. His confidence and descriptions of the company’s platform are company strategy, not evidence of market leadership or realized adoption.

Zinman expects organizations to adopt AI more slowly than the underlying technology changes. He argues that much business context is informal or undocumented, making an intelligent system harder to deploy effectively. His examples point to a need for human-agent collaboration and context gathering rather than a precise adoption timetable.

Stebbings asks about customer acquisition as search changes. Zinman says Google’s AI answers affected sponsored search clicks and estimates an impact of about 10% of Monday’s acquisition in terms of new ARR. That is his account of an acquisition metric, not a 10% decline in total company revenue; the interview supplies no independent attribution analysis.

He says Monday shifted spending toward other channels with longer sales cycles and had not seen the same impact across its other channels. The CEO’s causal explanation is plausible in his account but the discussion does not isolate other factors. He says the company announced an $870 million buyback program over approximately two to three years and had already repurchased some shares in the fourth quarter.

Asked why he has not personally bought shares, Zinman describes a prearranged trading plan and says any purchase would be a family decision. He estimates he retained more than 80% of his shares since the IPO and says he was not selling at the then-current price. These are his approximate holdings and intentions, not a prediction of a future purchase or share-price floor.

Zinman says the share-price decline affected him emotionally and cost him sleep. He tries to distinguish factors he can control from market sentiment and focus on execution. He describes relief at confronting a low valuation and a renewed willingness to take risks, while acknowledging the stock could fall further.

He illustrates his reasoning with approximate market capitalization, cash, enterprise value and ARR figures. These are his rough, time-specific estimates and use ARR, an annualized recurring measure, rather than recognized annual revenue. His metaphor that the market valued the business at “zero” expresses sentiment, not a literal financial calculation.

Stebbings asks whether private competitors have an advantage. Zinman thinks public-market scrutiny has forced his team to confront the magnitude of change, while private companies may be able to defer it. This is his perspective as a public-company CEO, not evidence that either ownership structure always produces better decisions.

Asked whether he wants to take Monday private, Zinman says no. He cites cash, positive free-cash-flow generation and retention as reasons the company does not need to raise funds. Those figures and descriptions are his account at the time; they are not a guarantee of future financial performance.

On acquisitions, he says Monday has considered companies but does not want its entire future to depend on buying a startup. He describes a gap between public and private valuations that can make stock-and-cash deals difficult. His examples are illustrative and do not disclose confirmed offers or the terms of any proposed transaction.

Zinman says conversations with other CEOs help, though people do not always reveal their emotions. His confidence comes from action and from the team led with co-founder Roy. He distinguishes acknowledging a problem from relying on reassurance that everything is fine.

He describes the personal strain of a difficult period and credits colleagues, his wife, children and extended family with supporting him. He says employees’ willingness to confront change gives him confidence. These are personal reflections, not evidence that a product pivot will deliver a financial outcome.

His main strategic bets are a horizontal agent-and-human workspace and rebuilding CRM and service offerings around agents. He views established competitors as capable but says each company must prove it can adapt. His expectation of an opening in those markets is a competitive prediction from a vendor with a direct commercial interest.

Zinman says smaller organizations may adopt new technology faster, while larger companies can find changing people and processes difficult. He cautions against underestimating incumbents and predicts investors may regain confidence if companies demonstrate acceleration. These are hypotheses about future adoption and valuations, not a verified market cycle.

In quick fire, he says the magnitude of AI’s effect on software is the belief he has changed most over the prior year. He also thinks he and co-founder Roy could explain Monday’s strategy better to investors. Better communication, he says, cannot replace execution.

Asked to choose between hypothetical investments in OpenAI and Anthropic, Zinman declines to identify a winner and emphasizes how rapidly perceived momentum changes. Stebbings describes investors seeking safety in cash; Zinman expects confidence to return through consistent results. Neither view establishes future market prices or investment returns.

He recalls advice from an investor during an earlier share-price rise: separate business performance from sentiment that can lift or depress a stock. Zinman says he tries to focus on revenue, retention and execution through cycles. His recollection is a leadership lesson rather than a reliable timing signal for a stock.

Zinman says he learns from other executives, including friends at Wix, and spends substantial time listening to interviews and other material. He frames continuous learning as necessary during rapid change. His favorable comments reflect personal relationships and are not a ranking of CEOs.

On marriage, he recalls a therapist suggesting that he tell his wife directly what her support has meant. He values communicating both positive and difficult feelings with family and work partners. His advice is personal and does not prescribe a single way to handle relationships.

In closing, Zinman expresses optimism that AI could improve services and quality of life, including access to help and expertise. These are hopes about the future, not evidence of a medical treatment or guaranteed benefit. He thanks Stebbings for the conversation.