A Founder’s Board of Directors: Six Tips for Success

See our Press Release Announcing all of our Promotions here.

Below you will find two notes from our newly promoted Partners:

Yash Hemaraj, BGV General Partner

Honored and thrilled to announce my promotion to General Partner at BGV, thanks to the unwavering support, trust, and collaboration of our incredible team and visionary founders.

A big thank you to our BGV and Arka Venture Labs portfolio companies and founders for inspiring me with your groundbreaking ideas and relentless passion for what you do. I am committed to being an enabler for your success, and I am excited to continue supporting you on your path to greatness.

Venture capital is a delicate balance of hope, optimism, awareness and caution. It requires us to be both aggressive and vulnerable. Over the past nine years, I have embraced the art of “transparent capital.” It means being honest with our stakeholders about expectations, having open conversations about opportunities and difficulties, and making decisions together. I am grateful to be surrounded by individuals who value this brand of venture capital.

My journey is defined by the extraordinary founders, co-investors, LPs, and my loving family who make all of this possible. I am humbled by the trust and support of our investors and partners, who have joined us in our pursuit of excellence. Your belief fuels my determination to identify and empower exceptional ventures that will shape industries, create better jobs, and transform lives.

Thank you for being a part of my journey, and I am incredibly excited for what lies ahead. Together, let’s continue driving innovation, making a positive impact, and shaping the future of venture capital.

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Sarah Benhamou, BGV Partner

I’m grateful and honored to be promoted to a Partner of BGV. When jumping onboard as an MBA intern in Israel in 2018, little did I know that this thrilling ride would lead me to managing European activities from a new office in Paris.

The VC industry has already changed a great deal in this short time, shifting from a period of irrational exuberance to a more diligent focus on sustainable growth and value creation. Navigating through these changes has been both challenging and rewarding, and I am grateful to share this journey with my experienced colleagues, who provide a rare showcase of discipline and methodical judgment while steering turbulent market fluctuations.

As I step into this new role, I am filled with optimism and enthusiasm for the future. Making a positive impact on society and the environment is a mission that resonates deeply with me, on a personal level, and I am fortunate to pursue this path professionally. BGV will continue to play a role in supporting purpose-driven ventures that drive both financial returns and meaningful change.

Throughout this journey, I’ve had the privilege of partnering with incredible talent and remarkable portfolio companies that sit at the forefront of enterprise innovation. These startups – including Madkudu, Zelros, Flytrex, Cryptosense and Kardinal – have continually impressed me with groundbreaking novelty, chastened by a disciplined grit and determination. Cryptosense, in particular, holds a special place in my heart as it marks my first successful exit as an investor, with its acquisition by SandboxAQ.

None of this would have been possible without the support of the Partners and team at BGV. Special thanks to them for their trust and for extending this opportunity, and also for being inspiring colleagues to learn from and work with!

What role should ethics play in investing in AI ?

That’s a question I have begun to hear more frequently as a general partner at BGV and as an investor who cares deeply about responsible tech and AI governance.

Imbedding ethics in company culture and product design can become a competitive advantage in AI first startups. By placing ethics at the core of product design, startups can accelerate market adoption by mitigating risks around bias, explainability and data privacy and continue to grow in an environment where values and ESG are becoming increasingly important with customers and employees.

A values-driven industry

At BGV, we invest in early-stage immigrant founders who are building AI-centric products for the Enterprise 4.0 market. Whether the technology is robotics, NLP, or computer vision, these organizations have deep tech at their core.

We believe that far more value can be created through AI use cases that augment humans rather than AI use cases that focus solely on replacing humans through automation. The former drives exponential growth in productivity while the latter commoditizes skilled labor leading to inequalities in income and wealth distribution.  AI used only for labor substitution may make sense for use cases that are dangerous (ie mining) or those where there is a shortage of labor (ie recycling).  That’s why we screen our deal flow to better understand the value creation impact rather than investing purely for automation use cases.  

We also screen founders for prior track record of transparency and ethical behavior. As early stage investors it’s vital that we can trust founders to deliver on their vision and promise.  At the end of the day the VC Business is about people, technology is a people business because we bet on the integrity and honesty of our founders as much as the innovations they are bringing to the world.

Red flags and green lights

During our due diligence process, we look for red flags and green lights.

What’s a red flag? How has a startup founder performed in his or her entrepreneurial career? Have they engaged in ethical behavior with customers? We also look at a founders’ past experience at established companies. If we find that he or she has a track record of not fulfilling their promises, that’s a big red flag for us.

The flip side of the red flag is the green light. If we find a startup entrepreneur has a consistent record of ethical practices and that their past customers and colleagues praise his or her leadership and integrity, that endorsement speaks volumes.

A human approach

We also believe that our founders have to trust us. It’s a two-way street. Our practice is to introduce a founders seeking an investment to other founders in our network. They need to do their own diligence on BGV and hear that we are a values based firm whose actions match the words, that we are truly committed to integrity and that we support our founders through the good and bad times.

That is vital, because as VCs we are building an 8-10 year relationship with a startup company. There will inevitably be ups and downs. Mistakes will be made. That’s why a relationship built on trust is at the core of our investing strategy.

Ethical AI governance strategy

There’s a difference between saying that you care about AI governance and actively engaging with startups to help them build responsible AI companies.  This is one of the reasons we founded EAIGG, a community platform of AI practitioners and investors dedicated to sharing AI governance best practices.

We have been pleasantly surprised that, indeed, many young entrepreneurs care about making the world a better place. Of course every young company wants to be a unicorn. But if a company’s values are lost along the way, and they are purely mercenary in pursuing their financial goals, then something important has been lost.

During our initial conversation with startup founders we ask them point blank: do you care about AI governance and data privacy ? Do you believe that AI can make humans expendable? We don’t expect that they’ll have everything figured out. But we do expect that the issues are important to them.

It’s important that startups have a roadmap for AI governance.  Because 10 years in the future, when the small startup has become a corporate brand, it’s nearly impossible to retrofit technology and product architectures for AI governance and data privacy.  This cannot be an afterthought.

A holistic view

When dealing with AI, it’s important to take a holistic view. I call this approach enlightened self interest. As a founder, it’s in the entrepreneur’s interest to build a great product. But it’s also in his or her interest to ensure market adoption, this implies ensuring elimination of model/data bias, addressing explainability and data privacy concerns to ensure that AI technology remains human-centric.

We’re excited about the promise of AI but we also believe it’s critical to put humans back in the equation. AI is projected to create $3 trillion of value over the next 10-15 years. Part of that equation is to contribute towards setting the guard rails so that AI development and deployment is democratized and creates value for both employees and owners of capital.

Investors need to prioritise the ethical deployment of AI – too much is at stake if they don’t.

Investors, take note. Your due diligence checklist may be missing a critical element that could make or break your portfolio’s performance: responsible AI. Other than screening and monitoring companies for future financial returns, growth potential and ESG criteria, it’s time for private equity (PE) and venture capital (VC) investors to start asking hard questions about how firms use AI.

Given the rapid proliferation and uptake of AI in recent years – 75 percent of all businesses already include AI in their core strategies – it’s no surprise that the technology is top-of-mind for PE and VC investors. In 2020, AI accounted for 20 percent or US$75 billion of worldwide VC investments. McKinsey & Company has reported that AI could increase global GDP by roughly 1.2 percent per year, adding a total of US$13 trillion by 2030.

AI now powers everything from online searches to medical advancement to job productivity. But, as with most technologies, it can be problematic. Hidden algorithms may threaten cybersecurity and conceal bias; opaque data can erode public trust. A case in point is the BlenderBot 3 launched by Meta in August 2022. The AI chatbot made anti-Semitic remarks and factually incorrect statements regarding the United States presidential election, and even asked users for offensive jokes.

In fact, the European Consumer Organisation’s latest survey on AI found that over half of Europeans believed that companies use AI to manipulate consumer decisions, while 60 percent of respondents in certain countries thought that AI leads to greater abuse of personal data.

How can firms use AI in a responsible way and work with cross-border organisations to develop best practices for ethical AI governance? Below are some of our recommendations, which are covered in the latest annual report of the Ethical AI Governance Group, a collective of AI practitioners, entrepreneurs and investors dedicated to sharing practical insights and promoting responsible AI governance.

Best practices from the ESG movement

PE and VC investors can leverage lessons from ESG – short for environmental, social and governance – to ensure that their investee companies design and deploy AI that generates value without inflicting harm.

ESG is becoming mainstream in the PE realm and is slowly but surely making its mark on VC. We’ve seen the creation of global industry bodies such as VentureESG and ESG_VC that advance the integration of sustainability into early-stage investments.

Gone are the days when it was enough for companies to deliver financial returns. Now, investors regularly solicit information about a fund portfolio’s compliance with the United Nations Sustainable Development Goals. Significant measures have been taken since 2018 to create comparable, global metrics for evaluating ESG performance. For example, the International Sustainability Standards Board was launched during the UN Climate Change Conference in 2021 to set worldwide disclosure standards.

Beyond investing in carbon capture technologies and developing eco-friendly solutions, firms are being pressed to account for their social impact, including on worker rights and the fair allocation of equity ownership. “Investors are getting serious about ESG,” headlined a 2022 report by Bain & Company and the Institutional Limited Partners Association. According to the publication, 90 percent of limited partners would walk away from an investment opportunity if it presented an ESG concern.

Put simply, investors can no longer ignore their impact on the environment and the communities they engage with. ESG has become an imperative, rather than an add-on. The same can now be said for responsible AI.

The business case for responsible AI

There are clear parallels between responsible AI and the ESG movement: For one thing, both are simply good for business. As Manoj Saxena, chairman of the Responsible Artificial Intelligence Institute, said recently, “Responsible AI is profitable AI.”

Many organisations are heeding the call to ensure that AI is created, implemented and monitored by processes that protect us from negative impact. In 2019, the OECD established AI Principles to promote the use of AI that is innovative, trustworthy and respects human rights and democratic values. Meanwhile, cross-sector partnerships including the World Economic Forum’s Global AI Action Alliance and the Global Partnership on Artificial Intelligence have established working groups and schemes to translate these principles into best practices, certification programmes and actionable tools.

There’s also been the emergence of VC firms such as BGV that focus on funding innovative and ethical AI firms. We believe that early-stage investors have a responsibility to build ethical AI start-ups, and can do so through better diligence, capital allocation and portfolio governance decisions.

The term “responsible AI” speaks to the bottom-line reality of business: Investors have an obligation to ensure the companies they invest in are honest and accountable. They should create rather than destroy value, with a careful eye not only on reputational risk, but also their impact on society.

Here are the three reasons why investors need to embrace and prioritise responsible AI:

1. AI requires guardrails

One only has to look at social media, where digital platforms have become vehicles that enable everything from the dissemination of fake news and privacy violations to cyberbullying and grooming, for a taste of what happens when companies seemingly lose control over their own inventions.

With AI, there’s still an opportunity to set rules and principles for its ethical use. But once the genie is out of the bottle, we can’t put it back in, and the repercussions will be sizeable.

2. Regulatory pressure imposes strong consequences

Governments worldwide are tightening digital regulations on online safety, cybersecurity, data privacy and AI. In particular, the European Union has passed the Digital Services Act and the Digital Markets Act (DMA). The latter aims to establish a safe online space where the fundamental rights of all users are protected.

The DMA specifically targets large platforms known as “gatekeepers” (think search engines, social media and online marketplaces), requiring them to be transparent in advertising, protect data privacy and address illegal or harmful content. Coming into effect as soon as 2023, the DMA can impose fines of up to 6 percent of annual sales for non-compliance, and as much as 20 percent for repeated offences. In extreme cases, regulators may even disband a company.

In a recent study on C-suite attitudes towards AI regulation and readiness, 95 percent of respondents from 17 geographies believed that at least one part of their business would be impacted by EU regulations, and 77 percent identified regulation as a company-wide priority. Regulators in the US and Asia are carefully following the progress made in Europe and will surely follow suit over time.

3. Market opportunities

It has been estimated that 80 percent of firms will commit at least 10 percent of their AI budgets to regulatory compliance by 2024, with 45 percent pledging to set aside a minimum of 20 percent. This regulatory pressure generates a huge market opportunity for PE and VC investors to fund start-ups that will make life easier for corporates facing intense pressure to comply.

Investors wondering about AI’s total addressable market should be optimistic. In 2021, the global AI economy was valued at approximately US$59.7 billion, and the figure is forecast to reach some US$422 billion by 2028. The EU anticipates that AI legislation will catalyse growth by increasing consumer trust and usage, and making it easier for AI suppliers to develop new and attractive products. Investors who prioritise responsible AI are strongly positioned to capture these gains.

Worth the effort

The call for investors to integrate responsible AI into their investments may feel like a tall order. It requires specialised talent, new processes and ongoing monitoring of portfolio company performance. Many fund managers, let alone limited partners, don’t yet have the manpower to achieve this.

But AI’s impending regulation and the market opportunities it presents will change how PE and VC firms operate. Some will exit, shifting resources to sectors with less regulation. Others, fortifying themselves against reputational risk while balancing internal capabilities, will add screening tools for AI dangers. Still, some will see responsible AI as Mission Critical.

Awareness is the greatest agent for change, and this can be achieved through adapting best practices on ethical AI governance from the community of start-ups, enterprises, investors and policy practitioners. Those that step up before it’s too late and who proactively help shape the rules as they are being written will reap the benefits – both economically and in terms of fuelling sustainable growth.

This is an adaptation of an article published in the Ethical AI Governance Group’s 2022 Annual Report.

Introduction

System integrators (SI’s) are the handmaidens between innovative startups and large enterprises. Both parties benefit from the relationship, as does the SI itself.

In my two decades-long business experience at Capgemini, however, I have noticed that startups do not always understand the role of an SI, how they can use these firms to their advantage, or how they must evaluate the pros and cons of the relationship.

System integrators include companies like Accenture, Deloitte, Infosys, TCS or Capgemini that are hired by large corporations to integrate component subsystems that drive automation, further digital transformation, and spur innovation across business platforms.

Startups or scale-ups must often work with SI’s to target an enterprise with their novel software solution. This can be a struggle, however, for solution providers that don’t have much experience working with SI’s or understand their relationship with the enterprise.

Understanding Value Against the Right Backdrop

Startups often offer a single-point solution, which can be of limited value if it cannot be integrated into an enterprise company’s broader IT infrastructure. Most enterprises rely on some level of outsourcing, and often depend on third parties to provide expertise in managing their information. This is precisely where a system integrator creates its value: helping the enterprise conduct an impact assessment to review how and where a given startup solution might be useful in the enterprise tech stack. Startups can benefit by doing some homework here as input to the assessment, which will help it to establish a clearer positioning in the context of the enterprise’s architecture.

Since enterprises often lack the in-house staffing required to fully explore the information landscape, a system integrator is called upon to manage IT infrastructure, conduct a digital transformation project, and/or to identify automation solutions that will keep the enterprise up-to-date. As a result, when an enterprise evaluates a solution offered by a startup, the company will often ask a system integrator for its guidance.

It’s of paramount importance, therefore, to understand the interests of the SI in this process and how these entities charge for their services. SI’s are fundamentally about deploying people and the SI will also assess the impact of the startup solution on its own economics.

SI contracts are typically structured in the following ways:

1. Service Level Agreement: If the SI is hired by way of an SLA, typically for ongoing managed services, the startup’s economics are aligned with that of the enterprise. Under this arrangement, the savings that a startup solution generates either funnels to the SI or is shared with the client. This alignment bodes well for the startup.
2. Fixed Price contracts, typically utilized for software development, are also fairly well aligned with the startup, although the SI will need to find ways to improve margin and improve quality of delivery. In these arrangements, the ability to scale is key.
3. Time and Material contracts, typically utilized for “resource provider” engagements, are those in which the SI is paid for the people it deploys to the enterprise – logged in time and material. This scenario is more complex for the startup vendor, as the economics may not align, and could even oppose the SI, which would lose billable hours with the enterprise if the startup solution is adopted by the enterprise. To make matters worse, many SI’s contract on this basis.

Enterprises will usually reveal the structure of their contracts with the SI. It is, therefore, incumbent on the startup vendor to understand the economic incentives of the SI, and work with that firm to discover how their input will improve the business case for the client (the enterprise) and benefit to the SI.

The Utilization Consideration

Utilization is a key metric for a system integrator.

Once a startup or scaleup has identified how its solution aligns with the business case of the system integrator, it must begin to explore the marginal value it offers. In other words, to successfully recruit the SI as a champion in the sales process, the startup vendor must demonstrate that the value it creates is worth the investment of the SI.

Consider that top system integrators deploy most of their staff on ongoing projects, and don’t have a deep bench of idle labor waiting for the next client. Therefore, if an SI is to expend time and energy to learn a new solution, evaluate it, stress test it, deploy it, and then train its team (and the enterprise) on this solution, the value must be clear.

If the SI doesn’t see the potential to deploy the solution broadly, and likely across a large base of its clients, then it could pose a challenge for the SI to justify the business expense of investing in that particular solution. The onboarding costs are rarely covered by one client.

The Pressure to Innovate

Another major driver for SI’s is the pressure to innovate. For an SI to justify its contract with the enterprise, it must demonstrate it has its finger on the pulse of the innovation landscape, and is equipped to deploy cutting edge technology solutions amongst at least some portion of its client base.  

Customers are increasingly savvy, so SI’s often feel pressure to offer new services and innovate whenever and wherever possible. For example, when the trend of Robotic Process Automation (RPA) surged, SI’s felt a keen pressure to learn and deploy these solutions, if only to burnish their innovation credentials and capabilities.  

When a trend is peaking and appears destined to win the future, this pressure toward innovation can override an SI’s direct economic interest. In rare instances, an SI might even adopt a solution and scale it up across its broader service offerings if only to demonstrate the firm’s forward thinking and bend toward innovative practices.

TCS, for example, drives billions of dollars of revenue each year from startups. They occupy one end of the spectrum, in terms of appetite for innovation. Others tend to follow the innovation curve, and only adopt new solutions if they’re offered by unicorn startups, or if they feel pressured or forced into action. Startups should research the SI to understand their appetite for innovation.  

The Cemetery of Proof of Concept: Bear the End in Mind

SI’s may sometimes leverage their enterprise clients‘ appetite for innovation, and do so in less constructive ways for startups.

Large SI’s enjoy a certain level of overhead from their enterprise contracts, who must justify their salary and value to their enterprise clients. After all, if an SI is hired to point their clients to innovative solutions and vendors, then a Proof of Concept (POC) with a startup vendor becomes an easy way to show an activity and justify a salary – even if the firm has no intention of ever truly adopting it. The cemetery of proof of concept is a classic (and very real) challenge for startups both with enterprises and SI’s.

Startups offering the POC must understand what it takes to move the concept into production, where it can ultimately generate revenue. Otherwise, a POC exercise can result in a costly showcase experiment with little prospect of graduating into a revenue-generating arrangement. When targeting a solution for an enterprise client, startups must identify which entity has requested the POC. It’s important to know whether the person on the enterprise or the SI side has the power to advance the POC to the next step.

Since POC’s are costly for startups to create, the founders must carefully evaluate the risk and reward of pursuing such an option. In certain instances, even if it’s clear to a startup that a POC has almost no chance of moving into production, but it may be worth pursuing it a) to gain exposure to the enterprise; b) to use it as a proof point with other potential clients; or c) simply to learn more about a corporation’s business processes and onboarding funnel.  

If, however, the POC is conducted simply to serve the SI’s innovation agenda, the startup may choose to charge the SI for serving as a consulting specialist. In that case, it’s important for the startup to be upfront with the SI, and vice versa. A startup must bear the end in mind and monitor the risk before entering into this kind of engagement.

Knowing When to Engage

SI’s tend to favor startup solutions that have an established Product Market Fit. Therefore, these firms prefer to engage with startup/scale-up vendors that have raised enough financing and have the ability to scale their solution broadly.  

If the startup is less mature, it would be wise to target the SI’s innovation program. That path will allow the startup to demonstrate the viability of its solution, showcase its architecture to targeted audiences, and provide a general exposure for the business on roadshows, podcasts, and conferences.  

The economics of joining an innovation program, however, may not be particularly compelling since they are not designed to create instant business outcomes. If the startup chooses to engage the SI at this stage, therefore, it may choose to work with the SI as a paid consultant, as previously discussed. For their part, SI’s tend to engage with startups with which they can see a scaling opportunity over the next 12 months.

Never Stop Selling  

Oftentimes, startup vendors underestimate the time it takes to secure a contract with an SI.  In fact, making the sale to an SI can be as long and laborious as dealing directly with the large enterprise. It takes time to build awareness, to entice a business unit within the SI to fall in love with your product, commit to it, and become your champion within the SI. In addition, other business units within the SI must buy in to escalate the sales process to the firm’s top echelon. But even after you’ve closed the contract with the SI, you haven’t finished your work.  

All you’ve accomplished is that you’ve secured the “right to sell.” This initial buy-in does not automatically generate outcomes. Startup vendors must continue to push the SI to implement and deploy its solutions with their enterprise clients. This means hands-on monitoring and relationship management to see the solution through to the deployment stages, and then tracking progress and customer success. This is the same process by which a customer success team works to ensure a client is successfully leveraging a tool to meet its goals.  

Conclusion

Selling into SI’s can be tremendously helpful to securing broad buy-in from large enterprise clients. These actors are uniquely positioned with the enterprise to adopt and deploy innovative automation solutions that are scalable, especially when related to IT infrastructure and digital transformation.  

However, the SI’s have their own unique challenges, and for a startup to successfully engage with an SI, it must not only understand the value of its solution within the target enterprise’s tech stack, but also have a clear view of the SI’s economics. To make a strong business case, the startup should be clear-eyed about where they sit on a particular SI’s priority list and its innovation agenda. The process can be challenging, but the rewards are mighty.