The urge to label one’s business as “AI-first” has grown immensely over the last few years, especially with the rise of generative AI tools that seem to promise success on autopilot. But too often, companies showcase an AI-focused image without actually embedding artificial intelligence into their core processes. It's a trap, and one I’ve seen too many businesses fall into.
As a European entrepreneur working at the intersection of AI, linguistics, and game design, I’ve navigated this terrain first-hand. What worries me most is how many startups, especially those led by underrepresented founders, overinvest in branding themselves as tech-first, all while neglecting the practical, iterative steps that real AI adoption requires. So let’s strip the fluff and dive into what it takes to avoid becoming an "AI-first” company with no genuine AI usage.
First, Let’s Clear the Misconceptions
Trending tools like ChatGPT and platform integrations make it seem like anyone can sprinkle AI into their business and call it a strategy. But the reality is, 83% of businesses don't fully deploy or effectively use AI, according to McKinsey’s 2025 survey on AI adoption. Offering chatbots or buzzword-filled pitches doesn't make you tech-savvy, it makes you a business propped up on appearances.
What Does Real AI Usage Look Like?
For AI to meaningfully support your operations, it must reach deeper than surface-level automations. Take Google’s blog on real-world AI, examples there detail how large systems integrate AI to process vendor proposals in minutes or use tools like Gemini to analyze customer trends. But these cases involve clear workflows, measurable impact, and proper team training, elements smaller startups often ignore.
I’ve worked closely with founders who confuse experimentation with implementation. That’s a mistake. Simply testing AI in one department doesn’t mean you’ve achieved anything truly transformative for your business model. Real adoption begins with these three key pillars:
- Training Teams Consistently: A platform doesn't solve problems; the people using it do. Without building confidence, even the best AI tools will sit idle.
- Small, Manageable Integrations First: Businesses should start small, automate one data-heavy process or replace repetitive tasks, then refine.
- Defining Success Metrics: Too many leaders measure success as "we launched AI," rather than tracking actual gains, be it efficiency, cost savings, or service improvement.
If you’re unsure about where to begin, guidance like BCG’s advice on preparing for the AI-first future is a solid starting point to define outcomes and ownership.
How to Avoid Common Mistakes
Embarking on an AI strategy without a plan is like building a ship with no blueprint. These are a few typical pitfalls I see regularly and how to sidestep them.
1. Skipping the Learning Phase
Many companies jump into purchasing AI tools without giving employees the time or space to understand them. When I started building AI-powered features for Fe/male Switch, a business simulation game for women in entrepreneurship, I made continuous team training non-negotiable. Everyone from marketing to operations learned how the technology connected to their tasks. That collaborative learning gave us clarity.
2. Expecting Rapid Wins
Growth takes time, no matter how “smart” the technology. Setting unrealistically high expectations creates friction among your team and your stakeholders. Data from Kyta, a platform supporting gradual AI adoption, shows businesses that roll out initiatives in phases have a 35% better implementation success rate than those going all-in from day one.
3. Neglecting the Human Factor
AI might eliminate mundane tasks, but people still drive decisions. Resistance occurs often when jobs feel threatened by automation. Instead, focus your messaging on empowering employees, AI isn’t replacing them but helping them focus on more complex, value-adding projects.
A Startup-Friendly Guide to Implementing AI
If you want to build genuine value without blowing your budget, follow these simple steps:
Step 1: Start With Data Cleanup
AI thrives on data. But if yours is messy, incomplete, or siloed, AI tools won’t work effectively. Dedicate energy to ensuring your datasets are pristine.
Step 2: Pick a Low-Risk Use Case
Don’t overreach. Could you save time by automating tasks like email responses or customer service? Tools like Canvanizer offer a way to brainstorm workflows small enough to test but impactful enough to measure.
Step 3: Embrace Analytics Before Creativity
Instead of generating flashy ideas, use analytics to track inefficiencies in your current system. Platforms like Dashboard.ai help pinpoint bottlenecks, which could highlight where AI solutions make the most sense.
Step 4: Measure, Review, Iterate
In our startup community, we review progress regularly. Using quantifiable metrics (e.g., processing speed increased by 28% or customer satisfaction improved via automated tickets), iterate based on what worked, not what looked good in theory.
Lessons From Europe, For Entrepreneurs
As a European entrepreneur, one thing I’ve noticed is the cautious adoption of new technology compared to the U.S. That’s not necessarily a bad thing, but it highlights how the pressure to “look” innovative rather than focus on substance is especially pronounced here. Many women I’ve coached in STEM startups share how their limited access to capital sometimes pushes them toward trends to attract investment, AI-first labels included.
If this resonates with you, my advice is: resist the temptation. Show investors incremental but measurable results from using AI, instead of grandiose promises.
Why Gradual Wins Matter
It’s easy to feel overwhelmed by tech hype or feel behind because your competitor rolled out an AI chatbot yesterday. But I believe that staying rooted in practicality leads to better results. The Superhuman AI blog outlines how simple metrics like “hours saved per team member” can reveal proof of impact better than broad claims about "AI transformation."
Concluding With Confidence, Not Hype
For female entrepreneurs in Europe and beyond, becoming overly focused on labels like “AI-first” could misdirect your energy and resources. Your goal should be building systems that genuinely support your work, solving real business challenges step by step. If you're unsure where to begin, check tools like Kyta for initial implementations or learn from insightful case studies by platforms like BCG.
Above all, as someone who has bootstrapped multiple tech startups, here’s my mantra: AI is a tool, not a magic wand. Treat it as such, and you might actually see it work for you.
FAQ
1. What does it mean to be an “AI-first” company?
Being an "AI-first" company means embedding artificial intelligence into the core workflows and decision-making processes of the business, rather than just adding surface-level integrations like chatbots. Learn more about becoming AI-first by BCG
2. What are the risks of labeling a business “AI-first” without meaningful AI usage?
Labeling your business as "AI-first" without genuine usage can misrepresent your capabilities, strain resources, and fail to solve real problems, leaving no measurable impact. Avoid the pitfalls of AI adoption
3. What are the first steps to adopt AI successfully?
Successful AI adoption begins with data cleaning, picking a low-risk use case for automation, team training, and setting measurable success metrics. Explore steps to implement AI using Kyta
4. How can startups utilize AI without overinvesting?
Startups should begin small by automating one repetitive process, leveraging proven tools, and iterating over time based on efficiency and cost-effectiveness results. Check out Superhuman’s adoption trends
5. Why is team training crucial for AI adoption?
AI tools are only as effective as the teams using them. Without training to build confidence and understanding, AI solutions often remain unused or underutilized. Learn from Fe/male Switch’s training strategy
6. What is a common mistake businesses make with AI?
A common error is expecting rapid results. Growth with AI takes time, and rolling out initiatives in phases increases the likelihood of success. Read about gradual adoption with Kyta
7. How can businesses measure the effectiveness of AI implementation?
Businesses can track metrics like increased efficiency, time saved, cost reduction, and improved customer satisfaction to assess AI’s impact. Explore real-world examples from Google’s AI cases
8. Why should startups focus on analytics before creativity in AI?
Focusing on analytics helps identify inefficiencies and prioritize tasks where AI will have the greatest impact, avoiding wasted resources on flashy yet unproductive projects. Discover tools like Dashboard.ai for analytics
9. How does human resistance impact AI adoption?
Fear of automation replacing roles often leads to resistance. Clarifying AI’s role as a tool for improving performance, not replacing workers, can ease these concerns. Find out how to manage AI-related workforce changes
10. Why is gradual AI adoption better than a rapid implementation?
Gradual adoption helps businesses refine processes, reduce risks, and build trust in AI systems, leading to long-term success. Learn more about gradual implementation strategies
About the Author
Violetta Bonenkamp, also known as MeanCEO, is an experienced startup founder with an impressive educational background including an MBA and four other higher education degrees. She has over 20 years of work experience across multiple countries, including 5 years as a solopreneur and serial entrepreneur. Throughout her startup experience she has applied for multiple startup grants at the EU level, in the Netherlands and Malta, and her startups received quite a few of those. She’s been living, studying and working in many countries around the globe and her extensive multicultural experience has influenced her immensely.
Violetta Bonenkamp's expertise in CAD sector, IP protection and blockchain
Violetta Bonenkamp is recognized as a multidisciplinary expert with significant achievements in the CAD sector, intellectual property (IP) protection, and blockchain technology.
CAD Sector:
- Violetta is the CEO and co-founder of CADChain, a deep tech startup focused on developing IP management software specifically for CAD (Computer-Aided Design) data. CADChain addresses the lack of industry standards for CAD data protection and sharing, using innovative technology to secure and manage design data.
- She has led the company since its inception in 2018, overseeing R&D, PR, and business development, and driving the creation of products for platforms such as Autodesk Inventor, Blender, and SolidWorks.
- Her leadership has been instrumental in scaling CADChain from a small team to a significant player in the deeptech space, with a diverse, international team.
IP Protection:
- Violetta has built deep expertise in intellectual property, combining academic training with practical startup experience. She has taken specialized courses in IP from institutions like WIPO and the EU IPO.
- She is known for sharing actionable strategies for startup IP protection, leveraging both legal and technological approaches, and has published guides and content on this topic for the entrepreneurial community.
- Her work at CADChain directly addresses the need for robust IP protection in the engineering and design industries, integrating cybersecurity and compliance measures to safeguard digital assets.
Blockchain:
- Violetta’s entry into the blockchain sector began with the founding of CADChain, which uses blockchain as a core technology for securing and managing CAD data.
- She holds several certifications in blockchain and has participated in major hackathons and policy forums, such as the OECD Global Blockchain Policy Forum.
- Her expertise extends to applying blockchain for IP management, ensuring data integrity, traceability, and secure sharing in the CAD industry.
Violetta is a true multiple specialist who has built expertise in Linguistics, Education, Business Management, Blockchain, Entrepreneurship, Intellectual Property, Game Design, AI, SEO, Digital Marketing, cyber security and zero code automations. Her extensive educational journey includes a Master of Arts in Linguistics and Education, an Advanced Master in Linguistics from Belgium (2006-2007), an MBA from Blekinge Institute of Technology in Sweden (2006-2008), and an Erasmus Mundus joint program European Master of Higher Education from universities in Norway, Finland, and Portugal (2009).
She is the founder of Fe/male Switch, a startup game that encourages women to enter STEM fields, and also leads CADChain, and multiple other projects like the Directory of 1,000 Startup Cities with a proprietary MeanCEO Index that ranks cities for female entrepreneurs. Violetta created the "gamepreneurship" methodology, which forms the scientific basis of her startup game. She also builds a lot of SEO tools for startups. Her achievements include being named one of the top 100 women in Europe by EU Startups in 2022 and being nominated for Impact Person of the year at the Dutch Blockchain Week. She is an author with Sifted and a speaker at different Universities. Recently she published a book on Startup Idea Validation the right way: from zero to first customers and beyond, launched a Directory of 1,500+ websites for startups to list themselves in order to gain traction and build backlinks and is building MELA AI to help local restaurants in Malta get more visibility online.
For the past several years Violetta has been living between the Netherlands and Malta, while also regularly traveling to different destinations around the globe, usually due to her entrepreneurial activities. This has led her to start writing about different locations and amenities from the POV of an entrepreneur. Here’s her recent article about the best hotels in Italy to work from.
About the Publication
Fe/male Switch is an innovative startup platform designed to empower women entrepreneurs through an immersive, game-like experience. Founded in 2020 during the pandemic "without any funding and without any code," this non-profit initiative has evolved into a comprehensive educational tool for aspiring female entrepreneurs.The platform was co-founded by Violetta Shishkina-Bonenkamp, who serves as CEO and one of the lead authors of the Startup News branch.
Mission and Purpose
Fe/male Switch Foundation was created to address the gender gap in the tech and entrepreneurship space. The platform aims to skill-up future female tech leaders and empower them to create resilient and innovative tech startups through what they call "gamepreneurship". By putting players in a virtual startup village where they must survive and thrive, the startup game allows women to test their entrepreneurial abilities without financial risk.
Key Features
The platform offers a unique blend of news, resources,learning, networking, and practical application within a supportive, female-focused environment:
- Skill Lab: Micro-modules covering essential startup skills
- Virtual Startup Building: Create or join startups and tackle real-world challenges
- AI Co-founder (PlayPal): Guides users through the startup process
- SANDBOX: A testing environment for idea validation before launch
- Wellness Integration: Virtual activities to balance work and self-care
- Marketplace: Buy or sell expert sessions and tutorials
Impact and Growth
Since its inception, Fe/male Switch has shown impressive growth:
- 5,000+ female entrepreneurs in the community
- 100+ startup tools built
- 5,000+ pieces of articles and news written
- 1,000 unique business ideas for women created
Partnerships
Fe/male Switch has formed strategic partnerships to enhance its offerings. In January 2022, it teamed up with global website builder Tilda to provide free access to website building tools and mentorship services for Fe/male Switch participants.
Recognition
Fe/male Switch has received media attention for its innovative approach to closing the gender gap in tech entrepreneurship. The platform has been featured in various publications highlighting its unique "play to learn and earn" model.
