The biggest financial risk for investors in the AI era, according to Arkin Digital Health

“As investors, the biggest financial risk is essentially the company not being able to scale,” explained Nadav Shimoni, Managing Director at Arkin Digital Health. “It is a major concern given all the vibe coding and lower threshold to build. In other words, we are seeing way more competitors coming in faster and creating a much more challenging sales cycle.”

Arkin Digital Health invests in the early stage of healthcare companies. Shimoni joined CTech for its latest series exploring how and why investing these days may be different from previous times in the past.

Nadav Shimoni arkin holdings

“A very big financial risk from our perspective is building in a place that is prone to dense competition that leads to the commoditization of your product,” he continued. “It is literally impossible to asses competitive landscape as it changes so dramatically so the question is really - why this company will shine? Why them and not others?”

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Fund ID
Name and Title: Nadav Shimoni, Managing Director
Fund Name: Arkin Digital Health
Founding Team: Nadav Shimoni, Managing Director
Founding Year: 2021
Investment Stage: From pre-seed to Series A
Investment Sectors: Healthcare

On a scale of 1 to 10, how has AI impacted your fund’s operations over the past year - specifically in terms of the day-to-day work of the fund's partners and team members?

8 - First and foremost, we are constantly learning and feel there are many opportunities we have yet to materialize, and therefore, I gave it an '8' and not '10'. Beyond that, we feel AI impact across the board, but far more internally in our operations right now.

Some examples: Utilizing AI to analyze more efficiently and quickly specific companies or segments, running models to better evaluate different scenarios/outcomes for investments, working more efficiently with our portfolio companies and network, and more.

Have you already had any significant exits from AI companies? If so, what were the key characteristics of those companies?

I must say I don't relate to the definition "AI companies". I think that, except for foundation model developers (OpenAI, Anthropic, etc), any company today is using AI. The question is how, where, and what the outcome of that utilization is. The rapid developments in AI are causing us to be even more rigorous in validating that there is actually a real business need and assessing if the company at hand is actually approaching this problem with what seems to be an efficient solution. Not the most sophisticated one, but the most relevant one.

What specific financial performance indicators (KPIs) do you examine when assessing a potential AI company? Are there any AI-specific metrics you consider particularly important?

One part is an extension to the previous answer. We are looking for real objective data from customers (either potential or existing ones) that proves there is actually a need on their end, and they see the solution as something they want to use/using it, and love it. Examples are active users, activation time (from contract signature to deployment to start using), sales cycle, etc. In healthcare, it is very easy to follow vanity metrics that make you think you have traction with customers when it is too soon to tell (example - contracted revenues and not live revenues).

Another part is operational efficiency. Over the last decade, too many companies raised too much money that went too many times to inefficient operations (essentially hiring too many people). We want to understand how companies build their budget, where they are using AI to reduce dependencies on full-time employees and to do more, faster.

How do you approach the valuation of early-stage AI startups, which often lack significant revenues but possess strong technological potential?

Trying to think about the size of the opportunity both in terms of market size and the type of relevant buyers (in other words, who can buy such a company and for what price, based on the acquirers and the segment history). Another factor is also the strength of the team and their ability to seize that opportunity.

What financial risks do you associate with investing in AI companies, beyond the usual technological risks?

First, there is a real issue with compute costs (that is similar to cloud costs - you start usually with relatively small utilization, usually given for relatively free by the cloud / AI vendor, but as you grow the business these costs also grow, dramatically).

But beyond that, as investors, the biggest financial risk is essentially the company not being able to scale. It is a major concern given all the vibe coding and lower threshold to build. In other words, we are seeing way more competitors coming in faster and creating a much more challenging sales cycle. Therefore, a very big financial risk from our perspective is building in a place that is prone to dense competition that leads to the commoditization of your product. It is literally impossible to asses competitive landscape as it changes so dramatically so the question is really - why this company will shine? Why them and not others?

Do you focus on particular subdomains within AI?

No. We invest across the board in early-stage software-based solutions for healthcare

How do you view AI’s impact on traditional industries? Are there specific AI technologies you believe will be especially transformative in certain sectors?

We are focused on healthcare, which is a very traditional industry. Historically it is very slow to adopt new technologies, yet now we are seeing an increased openness for new tools, driven by acute clinician burnout (>50% of clinical staff in the US!), much of it ironically exacerbated to date by poorly designed digital tools like EHRs, and also by growing financial pressures that commands more efficient operations. AI offers a rare opportunity to reduce the administrative overload, and maybe in the longer term, enabling smarter decision-making without adding workflow friction. For early-stage investors, the challenge, and opportunity, I think, is finding companies that deeply understand healthcare’s operational realities and can develop and integrate their products in an efficient, safe, and clear short-term ROI.

What specific AI trends in Israel do you see as having strong exit potential in the next five years? Are there niches where you believe Israeli startups particularly excel?

In today’s environment, there is no clear blueprint for how to best apply AI when developing new products, and as the pace of innovation is so high, it will only get worse. In this situation, the ability to think creatively and build lean, pragmatic solutions is a huge advantage. Arguably, this is the very core strength of Israeli founders and why we became Startup Nation. Doing more with less, through scrappy product-market iteration and clever use of foundation models, proprietary models and data streams, I'd say positions Israeli founders really well for breakthroughs that could lead to meaningful exits in the next five years.