5 real-life Business Process Automation examples for Corporate Strategy

5 real-life Business Process Automation examples for Corporate Strategy

Automation differs in corporate strategy because the function is low-volume and high-judgment, so the aim is rarely to automate the final decision.

Instead, automation is most useful for gathering market intelligence, tracking signals, synthesising internal and external data, building first-pass analyses, and keeping leadership aligned, which shortens strategy cycles while leaving prioritisation, trade-offs, and conviction with senior humans.

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Sector

Accelerated Deal Sourcing Automation in Private Equity and Venture Capital

Submitted by Frederic Kalinke

This AI Automation helps investment teams accelerate their deal sourcing by automatically analyzing company, industry, and performance metrics from pitch decks, enabling the review of 10× more opportunities through significantly faster and more efficient opportunity processing.

Use Case
Deal Sourcing
Tools
PitchBook, Grata
Input
Pitch Decks
Process
Automatically analyse company, industry and metrics
Output
Faster processing of investment opportunities
Outcome
Review 10× more opportunities
Private Equity and Venture Capital
Asset and Wealth Management
Corporate Strategy
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QuantumLight Aleph AI Deal Sourcing Model

QuantumLight deploy Aleph, a proprietary ML model trained on 10 billion data points from 700,000 VC-backed companies, to identify and recommend every investment the fund makes, removing human bias from venture capital decision-making.

Use Case
AI-Driven Startup Deal Sourcing
Tools
Internal Tools
Input
Data from over 700,000 VC-backed companies covering investor syndicate composition, lead investor quality, founder profiles, employee quality signals and funding round characteristics.
Process
Machine learning models score and rank growth-stage companies to identify statistical outliers, replacing emotion-driven and herd-mentality judgement with systematic quantitative analysis.
Output
Ranked investment recommendations surfaced to the team, with every deal made to date having been recommended by Aleph rather than sourced through traditional deal flow.
Outcome
All 17 Fund I investments were Aleph-recommended; back-tested performance reportedly outperforms 95% of VC funds, supporting a hard-cap close of the inaugural 250 million dollar fund.
Private Equity and Venture Capital
Corporate Strategy

Warren County's AI-Enabled Public Deliberation Platform

Warren County, Kentucky uses AI bots from Jigsaw (Alphabet) and statistical analysis from Polis to conduct large-scale resident consultations, surfacing areas of consensus to guide local government planning and reduce political polarisation.

Use Case
AI-Facilitated Civic Deliberation
Tools
Polis & Jigsaw (Alphabet)
Input
Open-ended conversational responses from approximately 10% of residents about local governance priorities, collected via AI chatbot interviews.
Process
Jigsaw's AI platform conducts extended individual conversations with residents, scans the full volume of replies to identify common themes, then presents candidate priorities back to participants for approval voting.
Output
A ranked consensus map of resident priorities, with approximately half of all ideas receiving over 80% approval, used directly to shape the BG 2050 Initiative strategic plan.
Outcome
The county produces a broadly supported, centrist governance plan while bypassing the dysfunction of traditional town halls, with over one million votes cast across the consultation.
Local Government
Corporate Strategy

S&P Global's M&A engine

S&P Global utilise a combination of Large Language Models to automate the identification of acquisition targets and the synthesis of vast datasets, allowing their strategy teams to evaluate potential deals with significantly higher speed.

Use Case
Automated Target Sourcing
Tools
Internal Tools & Google Gemini
Input
Global corporate datasets, unstructured market news, and financial filings.
Process
AI agents parse millions of data points to identify companies matching specific strategic criteria, while LLM-ready APIs allow for the rapid extraction of "connected insights" across disparate datasets.
Output
Curated lists of high-probability acquisition targets with automated rationale summaries.
Outcome
Faster decision-making cycles and the ability to evaluate a higher volume of deals without increasing headcount.
Asset and Wealth Management
Corporate Strategy

McKinsey's Lilli Internal Knowledge AI Platform

McKinsey deploys Lilli, a proprietary generative AI platform, to give its 45,000 consultants instant access to over 100,000 internal documents and interview transcripts. More than 72 percent of staff use it monthly, reducing research and synthesis time by approximately 30 percent.

Use Case
Consultant Knowledge Retrieval and Synthesis
Tools
Internal Tools
Input
Consultant queries about client sectors, comparable firms, expert recommendations, or project planning are entered via a conversational interface.
Process
Lilli acts as an orchestration layer across 40-plus proprietary knowledge sources, using large language models to retrieve, synthesise, and contextualise relevant insights and expert referrals.
Output
Summarised answers with source citations, relevant document links, and identification of internal subject-matter experts best suited to the engagement.
Outcome
Research and synthesis time reduced by around 30 percent, enabling consultants to redirect effort toward higher-value client interaction and problem-solving.
Management and Strategy Consulting
Corporate Strategy
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