Evgeniia Megrian is a founder-turned-business development advisor who has bootstrapped an EdTech startup, scaling it quickly to £100K in annual revenue and successfully exiting. Since then, she has worked with companies like Xsolla, Vivid Money, Sumsub, and Ultimate Guitar, helping them scale outbound growth through AI-powered automation.
Around a year ago, Evgeniia joined Semrush, a public MarTech company; after they saw the impact of an AI-backed business development tool she built.
How Did Everything Start?
After exiting my startup, I went deep into business development; not just as a strategy, but as an operational challenge. One thing stood out fast: in SaaS, even the most brilliant products often hit a wall when it comes to sales. Why? Because the pool of salespeople who truly understand niche tech is tiny.
Startups either grow too slowly or end up hiring generalists who can’t cut through the complexity of a real GTM motion. And in this space, where timing can make or break a deal, that gap was too costly to ignore, so I decided to build something that could fix it.
I built a sales expansion tool designed to help teams identify, engage, and scale the right sales talent faster. It’s now been used by 30+ startups and adopted by larger tech teams at Semrush, Xsolla, and Ultimate Guitar. It has helped accelerate global sales team growth and improve GTM velocity by over 40%, directly supporting market entry and pipeline coverage.
Today, I continue to work with scaling tech companies, contribute to the growth of digital business development practices, and share my learnings publicly through writing, mentoring and public speaking.
Everyone is Talking About AI – What Does It Mean To You?
For me, AI is a response to a very real problem in business development: how to scale commercial execution without blowing up your headcount or budget. I see it as a way to close execution gaps that have historically slowed down GTM teams: slow testing cycles, fragmented outreach, and guesswork around what works and where.
In the past year, I’ve been mapping how sales and business development functions are evolving across startups and mid-market tech companies.
One clear trend: the most successful teams aren’t just using AI to save time; they’re using it to make more strategic decisions. AI helps them prioritise high-value segments, personalise at scale, and move faster through market validation. It turns scattered commercial activity into something repeatable, measurable and scalable.
But what stands out even more is how AI is reshaping roles. Business development is shifting from manual hustle to systems thinking. Top teams now act like GTM architects, building lean, data-driven workflows that can adapt as they scale. AI gives lean teams the ability to test, iterate, and scale without needing layers of ops or analytics.
That said, AI isn’t a shortcut, it only works if the foundations are solid. If a company doesn’t understand its ICP, messaging, or market dynamics, no tool will fix that. But when those elements are in place, AI becomes a multiplier; helping teams reach further, learn faster, and execute smarter.
So to me, AI in business development is about precision and leverage. It’s not replacing strategy; it’s making it scalable.
You Have got Experience Building Startups; So What Advice Would You give To a New Founder?
Build distribution before you build complexity.
A lot of founders obsess over perfecting the product, but forget that even the best product doesn’t sell itself, especially in niche or crowded markets. I’ve seen this play out time and time again: teams spend months polishing features, only to hit a wall when it’s time to go to market.Start with a clear path to customers.
Figure out who you’re selling to, how they buy, and how you’ll reach them, before you scale your tech or team.
You don’t need a full commercial org on day one. What you do need is a way to validate demand and repeat the process. That’s where early business development matters most. Talk to customers early, test your messaging, and build systems that help you move fast when something clicks.
Also, don’t wait to systematise. Founders often think structure comes after traction, but I’ve seen the opposite: lightweight structure is what lets you move faster and make sharper decisions. Even basic frameworks for ICPs, outreach, or onboarding will save you time later and help you spot patterns earlier.
And finally, know when to zoom out. In the early stage, it’s easy to get pulled into daily sales or product fires. But your job is to keep the entire GTM machine moving forward, even when it’s scrappy. Great founders build momentum before they build departments.
How Much of a Role Does Software, SaaS and AI Play In Modern Day Startups?
Honestly, it’s everything. If you’re not building with software, scaling with SaaS, and moving faster with AI, you’re already behind.
In today’s environment, the old model: raise money first, then slowly build teams and processes doesn’t work anymore. Startups have to prove traction fast, often with smaller teams and tighter budgets. Software and SaaS make that possible: they’re not just supporting functions anymore, they are the operating system of modern startups.
Look at companies like Notion and Zapier, both built world-class businesses by scaling with minimal headcount early on, thanks to a sharp, SaaS-driven ops structure. They didn’t hire armies, they built systems.
And AI is reshaping how startups build go-to-market from the ground up. It’s the reason teams like Jasper AI were able to dominate their category in months, not years. It’s the difference between running 3 outbound experiments a month and running 30. It’s the reason lean teams can enter markets faster than legacy companies with 5 times the headcount.
But here’s the part I feel strongly about: tools only work if your thinking is clear. I’ve seen startups stack dozens of SaaS platforms without a real strategy behind them and all it creates is noise and slow decisions. Clubhouse is a good example: huge hype, tons of users, but no clear GTM system or adaptive growth model and the platform couldn’t hold momentum.
The startups winning today aren’t just buying tools. They’re building lightweight, repeatable GTM systems where software and AI amplify what’s already working, not compensate for gaps.
So to me, software, SaaS, and AI aren’t “nice to have” anymore. They’re the minimum requirement. The real advantage comes from how fast and how intentionally you layer them into your execution.
What Is the Single Most Important Piece of Digital Technology For Businesses Today?
Tools don’t scale companies. Adaptive teams do.
Today, the real advantage of digital technology is flexibility. It lets startups move faster: testing ideas, adjusting strategy and scaling without collapsing under complexity. A strong GTM system isn’t built once; it’s rebuilt and re-optimised every time the market shifts.
In early-stage and scaling companies, it’s slow reactions that kill momentum. Markets move quickly. Buyer behavior changes faster than teams expect. Technology like AI and automation only create real impact when they are tied directly to how teams learn and reframe their approach in real time.
You can see it clearly across the market. Slack started as a failed gaming company before adapting its internal chat tool into a SaaS success story. Shopify pivoted from selling snowboards to building the infrastructure for e-commerce at scale. Both teams spotted changing demand and rebuilt their go-to-market approach without waiting for a full product overhaul.
On the flip side, companies like Quibi spent heavily on product without building adaptive systems to learn from early user behaviour and collapsed within a year. Jawbone poured resources into tech innovation but failed to adapt to shifts in consumer health tech, while competitors like Fitbit stayed flexible and moved faster.
Working across SaaS, AI, and FinTech sectors, I’ve seen the difference clear systems make. Successful teams don’t chase every tool, they focus on building GTM engines that stay dynamic under pressure. They automate where scale demands it, stay personal where relationships drive deals, and adjust their motion without losing their edge.
What matters most isn’t the software you buy, it’s how you design your sales and business development infrastructure to stay flexible, resilient, and execution-focused. In the end, that’s the real competitive edge. Startups that master it scale. Startups that don’t stall.
Is No-Code Automation For Everyone?
It should be, but it’s not.
No-code automation has completely changed the game for startups. It gives small teams the power to build serious systems, revenue engines without needing engineering resources. With tools like Airtable, Zapier, Make, and Clay, a founder or a business development lead can now build scalable outbound funnels, customer onboarding journeys, or even lightweight CRMs without writing a single line of code.
You see it in companies like Zapier, Softr and Webflow; early teams that scaled because they baked automation into their DNA, not as an afterthought. Early teams in these companies moved fast because they understood that automation wasn’t about replacing people, it was about creating space to think bigger and execute faster.
But no-code only works if you think like a system builder. It’s not about connecting random tools. If you don’t know what your pipeline should look like, what signals matter, or how feedback loops flow back into the system, no-code just automates chaos. Fast.
I’ve seen it firsthand: startups that stack dozens of tools without clear process logic end up with fragile, messy backends that break under pressure. Clubhouse, again, is a great reminder, even when tech adoption is strong early on, weak operational systems can slow you down when the initial hype fades.
So no-code automation is incredibly powerful, it rewards structured thinking. Teams that have a clear commercial logic behind their GTM; the ones that know exactly what they’re optimising get a massive edge. The ones who don’t just automate bad decisions faster.
In short: no-code is for everyone who knows what they’re building toward. It’s not a shortcut it’s a speed boost for smart systems.
How Do You Utilise AI Without Losing The All-Important Human Connection Between Businesses and Customers?
You have to be clear about what AI should touch and what it should never replace.
AI is brilliant for scaling the invisible work: targeting smarter, personalising faster, qualifying leads, analysing patterns. It handles the background tasks that used to drain teams without adding real relationship value. But the mistake companies make is pushing AI too far into the customer experience itself trying to automate empathy, nuance, trust. That’s where the connection breaks.
We see it all the time: companies roll out chatbot-only customer service, thinking it saves time, but instead they frustrate users who just want a real answer. Think about how banks or airlines force you through endless AI menus when all you need is a two-minute human fix. Or B2B SaaS platforms where automated follow-ups feel robotic and generic, eroding any sense of real partnership.
In business development especially, AI should set the stage, not run the show. It can tell you which accounts to prioritise, suggest what messages to test, or help surface buying signals you might miss. But the actual conversations, negotiations and trust-building must stay human.
The best systems I’ve seen use AI to make the human moments sharper. They free up teams to focus where it matters: understanding pain points, co-creating solutions, navigating the emotional side of the deal that no tool can truly replicate.
If you use AI to eliminate friction without eliminating authenticity, you get the best of both worlds: speed at the system level, and trust at the relationship level. That’s the balance the best startups are getting right.
What Has Been Your Biggest Success To Date?
For me, it’s the full journey: starting from building my own digital product from scratch to creating systems that help global tech companies scale, not just in theory, but in some of the toughest market conditions we’ve seen.
Bootstrapping my EdTech startup, building the product, scaling it to £100K in annual revenue, and securing a successful exit taught me what it really takes to go from zero to traction. I didn’t have VC backing or a big team; I had to build a working product, validate messaging with real customers, and create a self-sustaining commercial engine almost immediately.
That experience shaped how I approach business development today, as a system that needs to move fast and monetise smartly.
But what I’m proudest of is how I took those lessons and applied them beyond my own company. Over the past few years, I’ve helped scaling tech firms like Semrush, Sumsub, Xsolla, AnnaMoney, and Ultimate Guitar build outbound sales systems that actually move the needle not in easy, hypergrowth years, but in an aggressive, resource-constrained market where slow execution could kill a company.
In particular, the AI-powered business development automation frameworks I developed helped teams reduce hiring and onboarding cycles by 50%, activate global GTM teams across APAC, EMEA, and LATAM, and close critical commercial gaps fast enough to secure key funding rounds and market entries. I worked directly with founders and sales leaders under pressure, where timelines were tight, traditional or scaling models simply wouldn’t survive.
Success, to me, isn’t just about building once. It’s about creating systems that can be reused, adapted, and scaled across products, markets, and teams. Systems that actually survive contact with the real world. That’s the work I’m proud of and that’s the impact I continue to build.
How Useful is LinkedIn For Businesses and is it Still Worth Using?
Absolutely, especially if you’re in business development, sales, or building commercial teams. LinkedIn today it’s one of the most powerful outbound engines for B2B companies if you know how to use it properly.
When it comes to connecting with the right salespeople, LinkedIn is still unmatched. It’s the only platform where you can filter by background, experience, industry focus, and buyer ecosystem and actually reach the decision-makers directly. In early-stage startups, where hiring the right first sellers or BD leads is critical, LinkedIn is essential.
I’ve personally built commercial teams across EMEA, APAC, and LATAM markets using LinkedIn as the main outbound channel. Around 80% of the salespeople hires I placed into scaling tech companies were sourced, engaged, and closed via LinkedIn outreach.
Beyond hiring, it’s also where early business development happens. Before a single formal meeting, founders, sales leaders, and prospects are already scanning your activity, positioning, and credibility. That first point of contact often happens long before an official outbound message.
The key, though, is using it intentionally. It’s easy to get lost in volume; chasing connections without building meaningful conversations. But when it’s tied to a real GTM or hiring strategy, LinkedIn delivers scale, trust, and access that cold email or ads alone can’t match.
So yes, LinkedIn is still incredibly valuable, not just as a social platform, but as a practical, high-impact lever for building and scaling B2B sales operations.
What Are The Pitfalls of AI (if any)?
AI is a powerful tool but like any tool, it magnifies whatever system it’s plugged into. That’s the biggest pitfall I see: teams treating AI like a solution by itself, when in reality it only accelerates what you’ve already built, for better or worse.
If your processes are broken, AI will just break them faster. If your GTM strategy is unclear, AI will help you scale confusion instead of results. I’ve seen companies rush to automate outreach, lead qualification, or onboarding without a real commercial logic behind it and instead of saving time, they burn trust.
A good example is early generative AI startups that flooded inboxes with poor-quality outreach templates, burning their market credibility before even reaching product-market fit.
Another major risk is over-automation where human connection should stay central. In business development especially, trust and nuance still close deals. You can see it with companies relying too heavily on chatbots, particularly in banking and telecom where scripted AI responses frustrate customers instead of solving problems.
The same happens in B2B SaaS when “personalised” sequences feel robotic, pushing prospects away instead of building real conversations.
Finally, there’s the risk of overfitting. Teams get so locked into patterns surfaced by AI that they stop questioning assumptions. AI is great at optimising based on past data but in fast-moving markets, sometimes winning means seeing the shift before the model does. Netflix faced this when its recommendation engine started reinforcing niche content bubbles while audience tastes shifted toward live, interactive formats like TikTok-style engagement.
In short: AI is powerful, but it doesn’t replace critical thinking, human judgment, or system design. It’s a lever, not a steering wheel. And if you don’t know exactly what you’re aiming for, it just helps you move faster in the wrong direction.
What’s Next In Your Opinion In the Digital World?
The next big shift is smarter, faster, and more modular go-to-market execution.
We’re moving past the first wave of “AI for AI’s sake.” Founders and sales leaders are realising that success isn’t about stacking tech, it’s about building GTM systems that can adapt in real time. Startups like Brex and Ramp are already moving this way: they build lean sales teams, automate 80% of the heavy lifting (prospecting, data enrichment, personalisation), and free up their human teams to focus only where it matters: closing high-complexity deals.
In the next few years, we’ll see even more companies abandon heavy, static commercial models. Instead of building big traditional sales departments, they’ll run micro-GTM teams: small, specialised squads that move quickly, test hypotheses, open markets faster, using AI not to replace teams, but to radically speed up market feedback cycles.
We’re also going to see human connection come back into sharp focus precisely because AI is automating the first layers of interaction. Companies like Gong and Chili Piper are building systems that automate scheduling, qualification, and routing but the real difference-maker is still who can build trust fastest once the conversation becomes real.
On the flipside, the companies that over-automate without strategy like some early B2B SaaS startups that relied too heavily on bots for demos and onboarding are already seeing higher churn and lower lifetime value, because customers notice when the relationship feels purely mechanical.
In short: the next edge in the digital world will belong to companies that can design adaptive growth systems, GTM models that are lean, feedback-driven, AI-augmented, but human at the key moments.
Slow is dead. In this new cycle, speed, precision, and real trust will decide who scales and who stalls.
