How Automated is the M&A Strategy Phase, Really?
This blog is in the Top 25 M&A blogs worldwide according to Feedspot
A look at 40 M&A tools and where they actually automate the strategy phase
In my last post I looked at where machine learning shows up in the M&A strategy phase. ML is only one slice of the automation question, though. The bigger and more practical question for a corporate development team or M&A advisor is simpler: if I want to run the strategy phase with software support, what can I actually automate today — and how deeply?
To answer that, I went broader. I mapped 99 M&A tools (38 of them assigned directly to specific actions in my M&A Reference Model) against every activity in the strategy phase, and counted two things separately:
Semi-automated support (blue in the chart) — the tool helps with the activity, but a human is still in the loop driving it.
Fully automated support (green) — the tool can execute the activity end-to-end without manual intervention.
The result is a histogram that tells a much sharper story than "AI is everywhere in M&A." Here is what the data actually shows.
Tool support is wildly uneven across the strategy phase
The first thing that jumps out is how concentrated the tooling is. Out of seven tasks, one — Finding potential targets — accounts for the overwhelming majority of all available automation. The bar for "Define selection criteria and market" alone reaches roughly 40 tools, and three of the four sourcing activities each have 15–25 tools.
The rest of the strategy phase is a different planet:
| Task | Approx. peak tool count | Fully automated tools |
|---|---|---|
| Finding potential targets | ~40 | A handful (sourcing only) |
| Processing the long and short list | ~22 | ~1 (indicative valuation) |
| Embedded M&A Strategy | ~5 | 1–2 per activity |
| Strategy Phase Project Management | ~4 | 1 (progress reporting) |
| Evaluation of the fit of a target | ~3 | 1 (cultural fit) |
| M&A Capability Map | 0 | 0 |
| Finalize and Approve Deal Proposal | 0 | 0 |
The market has converged hard on the easy half of the problem.
Semi-automation dominates — full automation is rare
The second pattern is just as important: almost everything is semi-automated, very little is fully automated. Across the entire chart, fully automated bars (green) are short stubs sitting on top of much longer semi-automated bars (blue).
The handful of activities where full automation actually exists tells you exactly what is automatable today:
Scan sources for potential targets — the biggest green bar in the chart. Pulling structured company data from public and licensed sources, scoring it against criteria, and surfacing candidates is genuinely automatable.
Embedded M&A Strategy activities — small green stubs across portfolio analysis, future strategy, and whitespace definition. These are likely LLM-driven analytical assistants rather than true autopilot.
Create indicative valuations — a thin green stub on top of a much larger semi-automated bar. Comps-based valuation models can run unattended; sanity-checking them still requires a human.
Check if the culture of the target fits — surprisingly, a small green bar. Almost certainly driven by NLP analysis of public signals (Glassdoor, LinkedIn, press, social).
Report on project progress — straightforward dashboarding.
Everything else that has tool support is semi-automated: the software does part of the work, a human still drives.
Where the real opportunity sits
Reading the chart as a buyer of M&A software, three observations stand out:
1. Sourcing is solved (or at least crowded). With ~40 tools competing on "define selection criteria and market" and 15–25 on the other sourcing activities, this is a mature, commoditizing segment. Differentiation here is increasingly about data quality and integration, not basic capability.
2. Fit evaluation is the most under-served high-value activity. Strategic fit, business model fit, operational fit, resource fit, ecosystem fit — each has only 2–3 tools, almost all semi-automated. This is where deal value is created or destroyed, and it's where the tool market is thinnest. The combination of LLMs + structured target data + buyer-specific context makes this the most interesting greenfield in the strategy phase.
3. The valuation gap is real. Indicative valuation has ~12 tools and exactly one fully automated offering. For software M&A specifically — where comps, ARR multiples, and Rule of 40 benchmarks are highly structured — there is room for serious fully automated valuation tooling. Most teams are still doing this in Excel.
What this means in practice
For an M&A team designing its tech stack today, the chart implies a clear allocation:
Buy for sourcing and longlist processing — the market is mature and you are not going to beat it.
Buy with caution for indicative valuation, shortlist processing, and embedded strategy support — useful tools exist, but expect to keep a human firmly in the loop.
Build or stitch for fit evaluation — the off-the-shelf options are thin; an internal LLM-based workflow over your target data is likely to outperform any single vendor.
Don't expect to buy capability mapping, deal-proposal workflow, or strategy-phase project management as M&A-specific products. Use general-purpose tools (Notion, Confluence, project management, internal portals) and accept that this is where your organization's M&A maturity actually lives.
Methodology note
The dataset is 99 M&A tools, of which 40 were assigned to specific activities in the M&A Reference Model strategy phase. For each tool–activity pair, I classified the support as semi-automated (human still drives) or fully automated (can run end-to-end). The histogram is a snapshot — vendor capabilities, especially in fit evaluation and LLM-driven analysis, are moving fast. I expect the green bars to grow meaningfully in the next refresh, particularly in the middle tasks.
M&A Reference Model © Dr. Karl Popp, 2026.
Parts of this post might be AI generated
