People – including those in the wealth management sector – need to be less beguiled by the hype around A1, and look at how traditional industries can be taken up another level, the author of this article argues.

It’s hard to avoid AI, and understandably, the media and wider world is fixated on it, swinging from optimism to dread. As understanding grows, and use cases in sectors such as private banking and wealth management take hold, hopefully, a calmer perspective will be in order. In this article, Denis Kalyshkin (pictured below), principal at I2BF Global, a venture capital firm, offers his perspectives. The editors of this news service are pleased to add this article to conversations that wealth managers and bankers must have, and we invite replies and suggestions. To enter the dialogue, email tom.burroughes@wealthbriefing.com and amanda.cheesley@clearviewpublishing.com Remember that the usual editorial disclaimers apply to views of guest writers.

Denis Kalyshkin

Forget the hype around AI-generated art, chatbots and productivity hacks. The real AI revolution is unfolding in the “boring” industries. Manufacturing, construction, agriculture, and healthcare might not be Silicon Valley’s favourite buzzwords, but they’re the bedrock of the global economy. And right now, they’re having a serious AI-powered upgrade.

A McKinsey report shows that 92 per cent of companies plan to invest in AI over the next three years. Meanwhile, the market for AI is forecast to soar to $115.4 billion by 2034. But there’s a twist: slapping AI into a company for the sake of it doesn’t cut it anymore. Value-driven, purposeful vertical integration is what counts.

The democratisation of AI means that everyone can use it – but not everyone can use it well. Much as the way in which SQL revolutionised CRM systems by tailoring data to business needs, AI's real power emerges when it is purpose-built for specific sectors. These vertical solutions are now the spearhead of innovation, dealing with real-world problems with precision.

What’s so “boring” about these industries?
If you think “boring” industries are irrelevant, consider this: manufacturing alone contributes 15 per cent of global GDP, rising to 25 per cent in some countries. Agriculture feeds the planet. Construction builds it. Healthcare keeps it alive. Their global revenues range from $5.5 trillion to $14.5 trillion. These are not side shows; they are centre stage. And they're ripe for transformation.

Here are some standout examples of vertical AI in action:

Manufacturing: Axion Ray
This startup uses predictive AI to identify equipment failures and quality issues before they occur. The result? Fewer breakdowns, fewer recalls, tighter schedules – and tighter margins.

Healthcare: Abridge
By turning doctor-patient conversations into structured medical notes using generative AI, Abridge slashes administrative overheads and enhances record accuracy. It’s clinical efficiency redefined.

Construction: Procore
Procore leverages AI to manage projects, ensure compliance and streamline workflows. It helps contractors keep costs under control and projects on schedule – a win in an industry where delays and overspending are notoriously common.

Agriculture: Cropin
An agri-intelligence platform that tracks crop health, predicts seasonal shifts, and safeguards yields, Cropin empowers farmers to manage weather risks and ensure supply chain consistency, crucial as climate unpredictability rises.

These startups are solving specific, billion-dollar problems in trillion-dollar industries. And they’re doing it with the help of sector-specific knowledge and cutting-edge tech.

Why vertical AI has the edge
Startups targeting these sectors are playing a smarter game, and here is why:

1. Market opportunity
Vertical AI is projected to hit $69.9 billion by 2034. Ready-to-use AI tools may offer surface-level solutions, but they lack the depth required to disrupt ingrained, complex workflows and solve niche problems. 

2. Premium pricing, better margins
Solving hard problems commands higher prices. These startups can charge a premium for their deep domain expertise, specialised tools, and tailored integration. Compared with horizontal platforms, gross margins can be up to 30 per cent higher – and lifetime value (LTV) grows accordingly.

3. Automation means efficiency
AI can automate labour-intensive, repetitive tasks – from data entry to compliance management. That means lower overheads and more scalability. Startups can grow without ballooning staff costs, improving cost-to-revenue ratios.

4. “Layer cake” product strategy
Start with one solution. Build a suite. By developing modular, stackable offerings, startups can increase annual contract value (ACV) and deepen customer relationships. It’s not just about solving one problem but becoming indispensable.

The hurdles that still matter
Of course, it’s not all smooth sailing. Traditional sectors come with baggage and startups must come prepared.

1. Legacy systems
Outdated infrastructure remains one of the biggest roadblocks. AI, built for unstructured data, often clashes with old-school enterprise systems designed for structured transactions. Poor APIs and incompatible data formats mean that integration isn’t just plug-and-play, so convincing risk-averse companies to switch to AI without hard ROI data is a tough sell. Deliver results fast and speak the language of impact, not innovation.

2. Domain expertise is non-negotiable
Technology alone won’t win. To gain trust and traction, startups must understand the industry’s culture, regulations, and pain points. Engineers who can translate code into construction lingo, or doctors who can double as product advisors, are worth their weight in gold.

Without this specific industry knowledge, expect resistance.

3. Fragmented markets
In sectors such as agriculture or construction, the landscape is dotted with small, local players. Reaching scale is a long game, requiring patience and persistence. Larger enterprise clients, meanwhile, may demand heavy customisation and long sales cycles.

Choose markets where the balance of readiness, size and willingness to adopt tech tips in your favour.

The bigger picture
Each month, we track Vertical SaaS deals in the US market – and the trend is clear: investor appetite for these targeted plays is growing. Why? Because they deliver. These startups are not just offering tech – they’re offering transformation.

Traditional industries don’t want another platform with generic features. They want tools built with them, and for them. Tools that understand the rhythm of their workflows and the depth of their problems.

Final word: The rise of unsexy innovation
AI’s future won’t be defined by viral demos or tech expos – it will be defined in factories, clinics, farms and construction sites. These are the places where real value is created, where inefficiency has billion-dollar consequences, and where AI has the power to reshape the world at scale.

Vertical AI is no longer a niche strategy, it’s the blueprint. As companies shift from generalist tools to specialist solutions, startups with the grit to understand and serve traditional sectors will be the ones that win.

Forget flashy. The future of AI is functional and it’s happening right where you least expect it.

About the author
Denis Kalyshkin is a principal at I2BF Global Ventures, a New York–based early-stage venture capital firm, and program manager at Pre-Seed to Succeed. With over 11 years of experience in investing across B2B SaaS, Industry 4.0, and DeepTech, Kalyshkin brings a unique perspective shaped by his earlier career as a rocket scientist. He is also a co-founder of a space technology research hub, bridging the worlds of frontier science and early-stage innovation.