Not an AI Company: How Non-AI Growth Firms Raise Capital

If it feels like every fundraising headline these days has an AI angle, you're not imagining it. And yet, 2025 wasn't just an AI story. McKinsey describes 2025 as the year dealmaking returned in force after three years of subdued activity. Buyouts surged, exits rebounded, IPOs came back, and megadeals returned, including a $55 billion take-private of Electronic Arts. AI is reshaping industry structures, bringing new competitors and promising big productivity gains. But here's the practical question for growth businesses in manufacturing, logistics, healthcare, consumer, and real assets: how do you raise capital when you're not an AI company? In this post, we'll break down where the money actually went, why AI is winning attention, not necessarily all the capital, what a non-AI raise has to prove, what that looks like sector by sector, how to compete for attention, and what to do if you're raising in the next 12 months. Let's get into it.

The Market Came Back in 2025, Just Not Evenly

McKinsey confirms it: 2025 saw dealmaking return in force after three years of quiet.

Here's the catch. The recovery is real, but the numbers that prove it sit in the largest transactions, not spread evenly across deal sizes or sectors. Buyout and growth deals above $500 million rose 44% to over $1 trillion, the highest year on record for that band, while PE-backed exit value rose more than 40%, helped by a near 100% jump in IPO exits. Those are large-cap figures. They don't describe a $30 million raise.

McKinsey's read is that this is structural, not a cyclical bounce. Shifts in deployment, returns, value creation and traditional fundraising "are more likely structural features of a maturing industry." Plan for a different market, not a re-run of the old one. Anecdotally, some family offices are reportedly moving earlier into deals, though the McKinsey data does not quantify this.

Honest expectation setting: a credible, cash-generating business can still get funded. The bar for proof has moved up, though, and the fight for investor attention is louder than it was.

Ahead, we cover where the money actually went, why AI is dominating the conversation, and what a non-AI raise has to demonstrate to get read at all, including the financing dynamics behind AI infrastructure.

Where the Money Actually Went: A Big-Deal Recovery

The headline number is big, and it belongs to the big end of the market. As established above, the 44% surge to over $1 trillion in buyout and growth deals above $500m was the highest year on record for that size band, according to McKinsey.

Across all buyout and growth sizes, deal value rose 17%. So growth was broad, but the shape of the recovery was not. Value climbed while buyout counts slid, which tells you where the weight sat: the largest transactions carried the year.

As established above, PE-backed exit value rising more than 40% alongside a near 100% jump in IPO exit volume signals a genuinely more open exit window. If your eventual buyer is a listed company, or the plan is to get there, that matters to you.

Now the caveat, plainly. Those figures cover deals above $500m. They say nothing quantified about the mid-market, and nothing at all about sector mix. Read them as a picture of the large-cap end, not as a description of your own round.

So here is the takeaway: there is liquidity and appetite in the system, and the exit window is genuinely more open than it was. But a $30m raise and a $500m raise are living in different data sets. Advisers working both ends of that gap say the same thing, and SENS Capital Partners are well placed to provide context and clarity due to our considerable track record and experience.

Why AI Is Winning the Attention, Not Necessarily the Capital

Which brings us to the loudest topic in the room: AI. It dominates deal flow and coverage. But attention and allocation are different things. Nothing in the research shows an AI premium or a discount applied to non-AI businesses, so make no valuation gap claim either way.

Building on that McKinsey framing from the intro, AI is reshaping industry structures, adding competitors and promising productivity gains.

Here's the practical version, and label it clearly as market observation rather than measured data: in practice, though no source measures this, investors have a finite number of hours, and a deal with an AI angle gets read first. That's a scheduling problem for a founder, not automatically a pricing problem.

What actually prices a deal? Cash generation, contracted revenue, asset backing and a credible path to exit. AI changes the competitive dynamics inside your sector. Treat that as a risk to answer, not a story to copy.

So reframe AI as a diligence question: how does it move your cost base, your competitors and your customer retention? Have a real answer ready. An AI-flavoured rebrand without that answer won't get you far. For more on how these dynamics play out across different capital sources, see our Further perspectives.

What a Non-AI Raise Has to Prove

Once you clear the attention hurdle, the diligence questions are refreshingly old-fashioned. Here is what your raise actually has to prove.

Earnings quality over narrative. Audited, reconciled numbers, plus a bridge from EBITDA to actual cash. Then one defensible answer on margins: why do they hold when input, labour or financing costs move?

Contract and demand visibility. Show contracted or recurring revenue. Disclose customer concentration honestly, with a plan to reduce it, and bring retention or repeat-purchase data only where it genuinely exists. Take a manufacturer with one customer at 40% of revenue: the plan matters more than the number.

Downside protection and structure. Give a lender or minority investor a defensible floor: hard assets, security, covenants, or mezzanine and structured credit. For asset-heavy businesses, that structure is the natural route rather than a fallback.

Capital intensity with a plan. A credible capex roadmap, split clearly between maintenance and growth spend. Then show the growth spend earns its cost of capital instead of just replacing worn-out kit.

Governance, depth and a named exit. A clean cap table, a board that can genuinely oversee the business, key-person risk addressed, and a view of who the natural buyers are and why they would pay. Nobody funds a business whose exit depends on hope. For a sense of how anchor investors weigh that before committing, what anchor investors bring to a raise is worth a read.

Get these five right and the sector conversation gets much easier, because the proof travels.

Sector by Sector: The Proof Each One Carries

None of the sources behind this piece break activity down by sector, so treat what follows as the questions a diligence team will ask, not as sector performance data.

• Manufacturing: utilisation and spare capacity, margin under input cost pressure, automation and energy exposure, supply chain resilience, and whether capex actually creates earnings.

• Logistics: contract density and duration, asset-light versus asset-heavy mix, exposure to freight rates and fuel, and how much margin rides on a handful of shippers or a single lane.

• Healthcare: reimbursement and payer mix, regulatory exposure, clinical quality, workforce retention, and the difference between a services business and one carrying real reimbursement risk on its own balance sheet.

• Consumer: brand durability beyond one product cycle, repeat purchase and cohort data, channel mix and reliance on discounting, plus pricing power measured against input and labour costs.

• Real assets: contracted or lease-backed income, cash yield versus headline valuation, refinancing exposure at current rates, and a realistic view of asset quality and residual value at exit.

None of that is a verdict on any sector. It is the checklist an investor will run before they run your model. Next: how to get that checklist in front of capital that already knows your sector.

How Non-AI Growth Businesses Compete for Attention

That question list from the sector section is also your pitch order. Competing for attention starts with picking the right rooms: sector-specialist funds, family offices with operating roots in the industry, institutions and sovereigns carrying real-asset mandates, and private credit lenders who underwrite cash flow rather than narrative. None of them need an AI gloss to get interested.

Then sharpen the story to one sentence an investor can repeat internally: what you do, who pays you, why it keeps happening and what the money does. If that sentence needs an AI wrapper to sound exciting, the sentence is the problem, not the market.

Lead the deck with the proof the market now asks for first. Numbers, contracts and the downside case before the growth chart gets a look. After that, run the raise as a process, not a mass email: a shortlist mapped to real mandates, a sequenced approach, and a data room that survives scrutiny on the first read.

Relationships shorten the path, and so does specialist help, particularly cross-border structuring when non-domestic investors are on the cap table and work conducted in confidence is part of how those conversations begin.

If You Are Raising in the Next 12 Months

Whatever your shortlist looks like by now, the next 12 months reward preparation over pitching. Five things to get right.

Fix the numbers before the deck. In practice, clean, reconciled financials and a working cash flow model are among the first things investors request. Get them audit-ready before anyone asks.

Match the instrument to the asset. Equity suits a growth business with little to secure against. Where there's a hard asset and predictable cash flow, structured credit or mezzanine often fits better, and prices better too.

Start the exit conversation early. With exit routes more open than at any point since 2021, a credible exit narrative now carries more weight with buyers.

A short, targeted investor list mapped to real mandates typically outperforms a broad email blast. The process runs on relationships and evidence, not contact volume. Where the capital sits outside the region, offshore structuring perspectives can shorten the path.

Prepare the AI answer before you're asked. How does it shift your costs, your competition and your customer retention? That's the question investors actually want answered, not whether you call yourself an AI company.

None of this is exotic. It's the same raise, sequenced better: proof first, instrument matched, exit framed early, list kept short, and an honest AI answer ready to go.

The Takeaway

The honest read for growth businesses in manufacturing, logistics, healthcare, consumer and real assets: liquidity is back, and selectivity is high. That mid-vs-large-cap gap established earlier still applies here: the recovery concentrated at the top, and a $30m raise competes in a more selective slice of that market.

AI is winning attention, not proven allocation. Nothing in the data shows a premium or a discount on non-AI deals. But investors read AI-flavoured decks first, so what closes is proof: cash generation, contracted revenue, downside protection and a credible exit.

So start there. Target capital that already knows your sector, whether that's a family office with operating roots in it or a private credit lender who underwrites cash flow. Bring in specialist help early if the clock matters, whether that's capital introduction, a private placement or cross-border structuring. If you're weighing institutional readiness, these perspectives on diligence readiness are worth a look before the first meeting.

Conclusion

The evidence is clear; what's left is execution.

Your next step: get diligence-ready before the first meeting. The perspectives on diligence readiness linked above are a smart place to start. Then move with intent, bring in specialist help early if the clock matters, and tell a clear story about how you make money and return it. You don't need an AI label. You need evidence, focus and momentum.