As of 2024, there are approximately 70,000 AI startups worldwide. The United States leads the global AI startup scene with around 5,749 startups, supported by significant investments, a robust talent pool, and a strong innovation ecosystem. China takes second place, and the UK ranks third. However, the total number of AI startups changes daily as new startups emerge and others evolve or exit the market. And according to the latest statistics, they do exit the market really often.
Approximately 90% of AI startups fail within their first year of operation. So, why do startups fail? There are different reasons for this. For instance, 34 percent of startups that fail report a poor product-market fit, while 22% falter because of inadequate marketing strategies. Team issues and financial problems account for 18% and 16% of failures, according to Growthlist.
In this article, we will not only delve into the reasons why do so many startups fail but extract valuable lessons from the most notable startup collapses. By understanding these pitfalls, both entrepreneurs and investors can better navigate the complexities of the AI industry. Whether you’re launching your own AI startup or investing in one, these insights will help you mitigate risks and increase your chances of success.
Common reasons for AI startups’ failures
Lack of market demand
Sometimes, a startup’s product or service does not meet a significant need or desire in the market, leading to insufficient sales and revenue. Around 42% of startups fail due to a lack of market demand for their products or services. Many AI startups fall into this category as they often create solutions in search of a problem rather than addressing existing market needs. For instance, Jibo, a social robot startup, failed despite significant media attention and initial funding. The company struggled to find a substantial market demand for its product, leading to its eventual shutdown in 2018. Consumers found the robot’s capabilities limited and not essential enough to justify the cost.
Inability to maintain a viable business model
The inability to maintain a consistent and viable business model means that an organization struggles to develop and stick to a strategy that effectively generates revenue and sustains operations. This often leads to financial instability, strategic confusion, and the eventual failure to achieve long-term goals. Olive A.I. failed due to its inability to maintain a consistent business model despite nearly $1 billion in funding and a peak valuation of $4 billion. The company faced financial difficulties, leading to layoffs of 665 employees between July 2022 and February 2023, and ultimately ceased operations in October 2023.
High development costs
Anki, a robotics and AI startup, created popular consumer robots like Cozmo and Vector. Despite raising nearly $200 million, the company struggled with high development and operations costs, coupled with insufficient revenue, leading to its shutdown in 2019. This issue is common, with many AI startups unable to sustain their financial needs in the long term. In fact, financial problems contribute to about 16% of all startup failures, illustrating the critical importance of sound financial planning and management.
Funding issues
Another big problem is funding. According to the most recent statistics, in 2023, the startup funding landscape experienced notable challenges and shifts. Global venture capital funding saw a significant decrease, dropping 42% from $381 billion in 2022 to $221 billion in 2023. This substantial decline deepens the difficulties startups face, making it increasingly challenging to attract investors and contributing to higher failure rates.
In April 2022, Chisel AI, a commercial insurance AI startup, announced its closure, citing macroeconomic pressures that hindered its ability to raise additional capital. The company detailed these challenges in a LinkedIn post, explaining that the economic environment made it impossible to secure the necessary funding to continue operations.
Team and management issues
Statistics reveal that around 18% of startups fail due to team-related problems, including management conflicts and human resource issues. Problems such as internal miscommunication caused by cultural code differences, lack of clear strategic direction, and poor leadership can severely undermine the startup’s operations.
Let’s recall the situation of OpenAI, which experienced significant internal conflict in November 2023 when the board unexpectedly fired co-founder Sam Altman, causing the company’s president, Greg Brockman, to resign in protest. This led to widespread confusion and backlash from employees and investors, with 700 of OpenAI’s 770 employees threatening to leave if Altman was not reinstated. After intense negotiations, Altman was reappointed as CEO with a new three-person board. This internal conflict at OpenAI showcases how team and management issues within a company can directly influence its operations.
Overestimation of AI capabilities
Believing in yourself is truly great, but you must always stay realistic. Seems like Rethink Robotics, known for its Baxter and Sawyer robots, unfortunately, wasn’t realistic. The company faced difficulties because its robots did not meet industry expectations for precision and reliability in performing tasks. Despite the initial hype and substantial investments, the robots failed to deliver the required performance in industrial settings. This mismatch between expectations and actual capabilities led to Rethink Robotics’ closure in 2018, teaching us and showing the importance of aligning technological promises with realistic outcomes.
Ineffective marketing
Did you know that 22% of startups fail due to poor marketing strategy? Effective marketing is essential to differentiate AI products in a crowded market, communicate complex technological benefits clearly, and attract the right audience. Without a strong marketing strategy, even the most innovative AI solutions may struggle to gain traction and achieve commercial success.
One notable example of a startup that failed due to poor marketing is Utrip. Utrip was a travel planning startup that used Artificial Intelligence and user recommendations to create highly personalized itineraries for its clients. Despite having an innovative approach and technology, Utrip struggled with marketing its services effectively. The failure to convey the value of its AI-driven solutions to potential customers led to inadequate user acquisition and retention, ultimately resulting in the company’s closure in 2019.
Weak cybersecurity protection
Neglecting cybersecurity can be catastrophic for AI startups, as they are prime cyberattack targets. Just in 2023, 46% of all cyber breaches impacted businesses with fewer than 1,000 employees, and cyberattacks targeted 61% of SMBs.
Approximately 6% of startup failures are attributed to tech-related issues, including poor cybersecurity and outdated technological solutions, and this involves not only startups but also big, established companies like CloudNortic, founded in 2007. In the summer of 2023, the Danish cloud hosting provider succumbed to a devastating ransomware attack obliterating its systems and customer data. Lacking the resources to pay the hackers (and as they said, even if they’d had those resources, they wouldn’t pay) or recover the lost data, the company had no choice but to shut down.
Top 5 lessons learned
Understanding the mistakes that lead to startup failures is crucial, but learning valuable lessons from these failures is even more important. By analyzing these lessons, startups can avoid common pitfalls and implement strategies that enhance their chances of success and sustainability.
Lesson 1: Importance of market research
Always find a problem first and then create a solution for it. One of our heroes of the inspiring article, Krish Ramineni, Co-Founder & CEO of Fireflies.ai, almost fell into the trap of not doing comprehensive market research by trying to create technology and then finding a problem to solve. His powerful lesson was that a business must identify a substantial, real-world problem first rather than creating a problem to fit a technology.
Let’s come back to Jibo, this social robot startup could have identified through comprehensive market analysis that there was insufficient consumer interest in a social robot with the capabilities it offered. By understanding consumer needs and desires beforehand, Jibo could have tailored its product to meet specific market demands, potentially avoiding its ultimate shutdown.
So what does effective market research involve?
- Identify customer needs and preferences: Understand the target audience’s needs and pain points to ensure the product or service meets market demands.
- Analyze market trends and competition: Assess current market trends, industry developments, and competitor strategies to position the business effectively and identify opportunities and threats.
- Evaluate market viability and opportunities: Determine the potential market size, growth prospects, and profitability to make informed decisions about product development, marketing strategies, and business expansion.
A dedicated team, including market research analysts, product managers, and marketing professionals, should conduct this research to ensure it aligns with product development goals.
The main idea is to solve existing problems by identifying consumer pain points first and creating value propositions that address these needs. Startups must focus on developing products that provide clear and compelling value to their target market, significantly increasing their chances of success.
Lesson 2: Managing funding and resources
When an AI startup gets funding, there is a high chance this money is spent on everything but not wisely, such as lavish office spaces, excessive hiring, or overly ambitious projects without clear revenue prospects. Effective financial management begins with meticulous budgeting and cost control, ensuring that funds are allocated wisely and efficiently.
Startups should develop a sustainable revenue model from the outset, focusing on generating consistent income streams rather than relying solely on initial funding. Regular financial audits and performance reviews can help identify potential issues early, allowing for timely adjustments.
And how to avoid high development costs and low revenue then? AI startups should focus on lean development practices, prioritizing the creation of a minimum viable product (MVP) to test the market before committing significant resources. They should also implement a phased approach to development, scaling up gradually based on proven demand and revenue growth. Additionally, startups must establish clear metrics for financial performance and adjust their strategies promptly based on real-world data and feedback.
Lesson 3: Building the right team
Steve Jobs once said, “Great things in business are never done by one person. They’re done by a team of people.” Diversity in software development is increasingly common nowadays and essential for fostering innovation and creativity. The team with the right mix of skills, experience, and cultural fit will always navigate the complex challenges of the tech industry effectively. However, once you assemble such a team, it’s very important to maintain healthy relationships within the team; promoting work-life balance and fostering a positive work environment is a basic minimum that every startup must implement to ensure the company’s success. In this case, a dedicated HR department is crucial in organizing the right work environment, preventing conflicts, and ensuring team members feel valued and supported.
Besides the atmosphere among the employees, effective team management also means a lot. According to recent statistics, teams with effective managers see a 29% increase in profits due to better recognition of quality work and achievements. It involves clearly communicating goals, using project management tools such as ClickUp or Monday.com, regular KPI reviews, and collaborative decision-making tools. The right people combined with effective management drive productivity, saving a startup from failure.
Lesson 4: Don’t neglect cybersecurity
According to the Allianz Risk Barometer, 45% of experts consider cyber incidents the most concerning threat to business operations. This level of concern is even higher than the worry about other potential causes of business interruption, such as natural disasters or energy-related issues. Cyberattacks always result in significant financial losses, reputational damage, and operational disruptions, potentially derailing even the most promising ventures.
To secure your startup:
- Begin by conducting comprehensive risk assessments to identify vulnerabilities and prioritize security measures.
- Update and patch software regularly to defend against known exploits and employ advanced threat detection systems to monitor suspicious activity.
- Educate your team about cybersecurity best practices, including recognizing phishing attempts and maintaining strong, unique passwords.
Encrypting sensitive data and implementing multi-factor authentication can further bolster security. The stakes are even higher for AI startups, where proprietary algorithms and data are critical assets. A breach could compromise intellectual property and competitive advantage. Investing in cybersecurity is investing in your startup’s future stability and credibility.
If dealing with cybersecurity seems too harsh, consider hiring a Chief Information Security Officer (CISO). 44% of business leaders already recognize the crucial role of CISOs in communicating complex cybersecurity issues in a way that non-technical executives, such as CEOs and board members, can understand. CISOs help ensure that top executives are informed about cybersecurity risks and can make well-informed decisions to protect the organization.
Lesson 5: Establishing a powerful marketing strategy
You can have the best product in the world, but if nobody knows about it, it’s all senseless. For example, gaming industry startups face a 50% failure rate due to poor marketing, a weak online presence, and rapid expansion risks. Quite a lot, huh? Moreover, online presence is not enough, it’s crucial to be able to effectively differentiate itself from larger competitors in the market.
- Understand your UVP (unique value proposition): Startups must clearly identify and communicate their unique value proposition. What makes your product different and better than the competition?
- Invest in market research: Comprehensive market research is essential to understand your target audience’s needs and preferences. The abovementioned startups could have benefited from deeper insights into customer pain points and the competitive landscape. Use surveys, focus groups, and competitor analysis to tailor your marketing strategy effectively.
- Build a strong brand identity: Brand identity helps create a memorable impression and builds customer loyalty. Remember – consistency across all marketing channels reinforces brand recognition.
- Use Digital Marketing channels effectively: Startups should harness the power of SEO, SMM, email campaigns, and content marketing to reach and engage their audience.
- Track and analyze marketing performance: By analyzing data on user engagement, conversion rates, and customer feedback, startups can identify what works and what doesn’t, allowing for continuous improvement.
