Private Equity Companies Join The AI Revolution

Private Equity’s Evolving Landscape

Private equity portfolio companies face numerous challenges, including integrating AI technologies, achieving business objectives, attracting top talent, and blending human capital with tech innovations. This article explores how AI can transform private equity portfolio companies, offering strategies to overcome these hurdles. Real-world case studies and data analysis highlight AI’s potential to drive success.

The AI Revolution: Innovators, Laggards, and Adapters

“At the heart of capitalism is creative destruction.” — Joseph A. Schumpeter

The AI revolution is transforming business by automating tasks, optimizing decisions, and unlocking innovation. For private equity portfolio companies, AI provides a competitive edge. Accenture found that scaling AI could double cash flow by 2035.

Jobs Most Impacted by AI

• Customer Service Agents: AI chatbots handle standard customer queries and complaints. AI chatbots represent one of the most successful use-cases of the AI revolution. Products like Zendesk’s Answer Bot have reported a 70% reduction in response times.
• Digital Marketers: AI optimizes marketing strategies. AI-driven platforms like Albert.ai can autonomously manage and optimize campaigns, increasing marketing ROI by up to 50%.
• Salespeople: AI qualifies leads and predicts future buying trends. Salesforce’s Einstein AI can boost sales productivity by 20%.
• Accountants and Financial Analysts: AI performs market analysis and risk assessment. Deloitte’s financial AI tools have reduced audit times by 50%.
• Software Developers: AI coding assistants like GitHub Copilot can suggest code snippets, increasing developer productivity by up to 55%.

The Value Proposition of AI

AI tools now generate insightful work across market analysis, risk assessment, and investment strategy. McKinsey estimates AI could add $15.7 trillion to the global economy by 2030, boosting GDP growth by 1.2%. This shift frees employees for higher-level work, spurring innovation and productivity. For instance, JPMorgan’s Contract Intelligence (COiN) reviews 12,000 credit agreements in seconds, a task that took 360,000 hours yearly.

Navigating the AI Adoption Journey

To stay competitive, private equity portfolio companies must act swiftly and strategically:

• Embrace AI Tools: Identify high-impact use cases and deploy AI to automate routine tasks, enabling employees to concentrate on strategic initiatives.
• Prioritize Upskilling: Invest in training programs to help employees develop the skills needed to work alongside AI, boosting their productivity and value.
• Ensure Responsible AI Deployment: Implement robust governance frameworks and transparency measures to mitigate bias, protect privacy, and maintain public trust.

Overcoming Critical Challenges with AI

“The world’s most valuable resource is no longer oil, but data.” — The Economist

Achieving Business Objectives

• Leverage Predictive Analytics: Anticipate market shifts, customer needs, and threats. General Electric saved $50 million using digital twins and AI to optimize wind turbine placement, boosting energy output by 20%. 
• Implement AI-Powered Performance Management Systems: Track KPIs, identify improvement areas, and enable data-driven decision making. Domo’s platform helped a major retailer increase revenue by $200 million with real-time insights across 11,000 stores.

Attracting and Retaining Top Talent

• Cultivate an Innovative, Learning-Focused Culture: Value creativity, collaboration, and growth. Airbnb retains 90% of employees by using AI for personalized career development and mentorship matching. 
• Provide Competitive Compensation, Benefits, and Perks: Prioritize employee wellbeing and work-life balance. LinkedIn reduced attrition by 50% through AI analysis of employee sentiment and targeted retention strategies.

Integrating People and Technology

• Conduct Comprehensive Assessments: Identify skills gaps, cultural barriers, and infrastructure needs. Bank of America upskilled 3,000 employees in AI and machine learning through its AI Curriculum initiative. 
• Develop Phased Implementation Roadmaps: Ensure clear communication, training, and support at every stage. Morgan Stanley achieved a 90% adoption rate for its Next Best Action AI tool by involving financial advisors in the design process and providing extensive training.

Real-World Success Stories

The AI revolution is already supplying the market with compelling data to support the immense impact it can have on private equity firms. Ginni Rometty has said, “Some people call this artificial intelligence, but the reality is this technology will enhance us. So instead of artificial intelligence, I think we’ll augment our intelligence.” 

• Siemens used AI for predictive maintenance, reducing downtime by 50%, increasing productivity by 25%, and saving €10 million annually.
• H&M’s AI chatbots handle 60% of customer inquiries, boosting satisfaction by 40% and saving $10 million in support costs.
• Ant Group’s AI algorithms assess creditworthiness, providing microloans to over 29 million underserved customers.

Conclusion

The AI revolution is not on the horizon; it is already here, reshaping industries and redefining what is possible. For private equity portfolio companies, the choice is clear: Embrace AI or risk obsolescence. By harnessing the power of AI to automate tasks, optimize decision-making, and augment human capabilities, private equity firms can propel their portfolio companies to new heights of success. The path forward requires a strategic blend of visionary leadership, continuous learning, and responsible innovation. Those who act decisively and adapt swiftly will not only weather the disruptive impact of AI but will also seize the extraordinary opportunities it presents. The future belongs to the bold—and it is written in code.

REFERENCES

1. Zendesk’s Answer Bot: This AI chatbot has significantly improved customer service by being available 24/7, which allows customers to receive quick responses anytime. This availability and efficiency in handling queries have transformed how businesses manage customer interactions, leading to faster response times and enhanced customer satisfaction. More details can be found in Zendesk’s resources here.

2. Albert.ai’s Impact on Marketing: Albert.ai has demonstrated its ability to autonomously manage and optimize marketing campaigns effectively. It uses machine learning to analyze data, optimize campaigns, and improve customer engagement significantly. This can lead to a substantial increase in ROI, with one instance showing a 16.3% improvement in YouTube ROI for a leading CPG marketer. Detailed insights into Albert.ai’s capabilities during the AI revolution can be explored here.

3. Salesforce’s Einstein AI: This AI tool enhances sales productivity by 20% through efficient lead qualification and trend prediction. Einstein AI leverages AI to provide sales teams with insights that help them focus their efforts more effectively and close deals faster. More information on Salesforce’s Einstein AI can be found on their official site.

4. Deloitte’s AI Solutions: AI applications in accounting and financial analysis, like those developed by Deloitte, have significantly reduced the time needed for audits. By automating complex data analysis, these tools allow financial professionals to focus on higher-level strategic decisions. Deloitte’s advancements in the AI revolution can be reviewed here.

5. GitHub Copilot: This AI tool assists software developers by suggesting code snippets, which enhances their efficiency by up to 55%. Copilot’s ability to automate routine coding tasks allows developers to devote more time to complex problem-solving and innovative projects. More about GitHub Copilot can be found on their product page.

6. McKinsey & Company on AI’s Economic Impact: McKinsey Global Institute estimates that AI could potentially add about $13 trillion to the global economy by 2030, which would enhance annual global GDP growth by approximately 1.2%. This prediction highlights AI’s capacity to significantly boost overall economic productivity, comparable to major technological advances of previous centuries. For more detailed insights and context, you can read more on McKinsey’s analysis here.

About the Author

Ken Gavranovic is a highly accomplished executive and thought leader with an impressive track record of spearheading successful acquisitions and driving transformative growth in both public and private companies. As the CEO of Actionable, Ken draws on his vast experience, having stewarded 1 IPO, 3 public companies, 35 M&A integrations, and 18 exits. In his previous role as EVP & GM at New Relic, Ken led M&A efforts, reporting directly to the CEO. With a multifaceted background spanning CEO, CMO, CRO, CPO, and CPTO roles, Ken brings unparalleled insights and expertise to every aspect of leadership and organizational transformation. His hands-on approach, strategic vision, and deep industry knowledge make him a sought-after advisor for companies looking to unlock their full potential through M&A and AI-driven innovation.

PS
Software engineers are hard to find, recruit, and compensate. Once you hire them, you risk knowledge being lost when they leave. AI software engineers can increasingly solve specific issues on their own, allowing human engineers to focus on domain rules and high-level problems. I was asked for a list of some great tools so see below.

1. Pick Your Niche

AI Coding Assistants:

• CodePal: Dozens of AI code generation tools.
• CodeWP: AI chat and coding tools for WordPress creators.
• GitHub Copilot: The world’s most widely adopted AI developer tool.
• Bito: Accessible, accurate AI tools trusted by developers across the world.
• Amazon CodeWhisperer: Your AI-powered productivity tool for the IDE and command line.
• Tabnine: Private and personalized AI coding assistant.
• Codeium: The most intelligent AI code generation tool.
• Sourcegraph Cody: Search, write, and understand code fast.
• CodeGPT: AI code chat, auto-completion, explanation, error-checking, and more.
• AutoCode Pro: Build Chrome extensions, web, and mobile apps from text.
• AlphaCode: Competitive programming tool with critical thinking, logic, algorithms, and more.

Open-Source AI Coding Assistants:

• Sourcery: Continuously refactors your Python code.
• Refact: AI coding assistant with blazing-fast code completion, editing, and chat.
• Continue: Generates, refactors, and explains entire code sections.
• ReactAgent: Generate React UI code from user stories.
• bloop: Helps teams modernize, write, and understand COBOL code.
• CodeGeeX: Powerful AI assistant for developers.
• Tabby: Open-source, self-hosted AI coding assistant.

AI Software Engineers:

• Fine: AI software developers that never sleep.
• Sweep: AI Python junior developer.
• Devin: The world’s first fully autonomous AI software engineer.
• Devika: Open-source AI software engineer that understands high-level instructions.
• smol.ai: Junior developer AI agent that turns plain text into apps.
• AutoDev: AI agents that work together to complete complex software engineering tasks.
• SWE-Agent: Open-source Devin alternative that autonomously solves issues in GitHub repos.

2. Build Your App

Plugins for Popular Code Editors:

• Tabnine: Works with 15 code editors.
• Codeium: Works with 40+ code editors.
• Codebuddy: Works with 16 code editors.

AI Agents for Autopilot Coding:

• Devin: Can do Upwork gigs on autopilot.
• CodeGPT: Can handle coding tasks on your behalf.
• ReactAgent: Builds React components from user stories.
• Fine: Has AI agents that understand, analyze, generate, and test code.

Train Your Own Model:

• Tabnine: Trained on open-source repositories.
• Refact: Combines its custom and third-party AI models.
• GitHub Copilot: Trained on all languages from public repositories.
• CodeWP: Offers AI chat and coding tools trained for WordPress creators.

Chrome Extensions for Coding Tasks:

• CodeSquire: A code assistant for data scientists.
• CodePal: Has a Chrome extension with 12 coding tools.
• AI2sql: Helps you write complex SQL queries.

AI-Powered Micro-SaaS for Niche Development:

• Relicx: Lets you write stable tests faster.
• Snyk: Helps to secure AI-generated code.
• Theneo: Generates Stripe-like API docs in seconds.
• Mutable.ai: Turns code into wiki-style knowledge bases.
• Grit: Helps with code migrations and dependency upgrades.

All-in-One Coding Assistants:

• Replit AI: Can complete, generate, edit, document, and explain code.
• CodeGPT: Can write, complete, refactor, document, test, and interpret code.
• CodeGeeX: Can generate, autocomplete, comment, translate, and chat with code.

Support Multiple AI Models:

• AskCodi: Uses OpenAI’s GPT-3.5-Turbo and GPT-4.
• CodeGPT: Uses GPT-4-Turbo, Gemini, Llama2, Claude, Mixtral, and more.
• smol.ai: Fine-tuned GPT-3.5 models to be up to 10x faster than GPT-4. It also has fine-tuned CodeLlama-34B models that can beat GPT-4.

APIs for Integration:

• CodePal: Has an API for code writers and helpers.
• CodeGPT: Lets you integrate it into your custom projects via an API.
• AI Query: Helps you generate, explain, and optimize SQL queries.

AI Startup Accelerators:

• smol.ai: Part of Vercel’s AI Accelerator.
• Sweep: Part of Y Combinator’s Batch S23.
• Aide: An AI-native, privacy-first IDE for VSCode, part of Y Combinator’s Batch S23.

3. Pick Your Monetization Strategy

Charge Per User:

• Codacy: Costs up to $18 per user/mo.
• Tabnine: Costs up to $39 per user/mo.
• AskCodi: Costs up to $29.99 per user/mo.

Subscriptions:

• Sweep: Costs $480 per month.
• Replit AI: Costs $20 per month.
• Fine: Costs up to $99 per month.

Monetized Open-Source Tools:

• Sweep: Has open-source and pro versions.
• Refact: Has open-source and cloud versions.
• CodeGeeX: Has open-source and paid enterprise versions.

Value Ladder with More Powerful AI Models:

• CodePal: Offers advanced models on the enterprise plan.
• Aide: Offers Claude Opus and DeepSeek Coder 33B on the paid plan.
• Bito: Offers GPT-3.5 on the free plan and GPT-4 with Claude on the paid plan.

Enterprise Plans:

• Aide: Has an enterprise plan with self-hosting options and 24/7 support.
• Refact: Has an enterprise plan with fine-tuned models, code privacy, better controls, and more.
• Sourcegraph Cody: Has an enterprise plan with flexible deployment, multi-repo context, and more.

Add-Ons:

• Tabnine: Sells an optional add-on to fine-tune the models on your code.
• GitHub Copilot: Plans to sell an add-on to fine-tune its AI on your codebase.
• Fine: Sells custom AI agents as an add-on starting at $500 per month. It also sells more processing power starting at $10 per month.

Usage-Based Pricing:

• Codebuddy: Plans with 600-10,000 monthly AI credits.
• AskCodi: Plans with 50, 500, and 3,000 monthly AI credits.
• CodePal: Get up to 10,000 AI monthly requests for $243 per month.

Bundle Solutions:

• Sourcegraph: Bundles its coding assistant and code search products.
• Codacy: Bundles its coding assistant with code quality, security, coverage, and data solutions.
• Elegant Themes: Bundled DIVI and DIVI AI to offer WordPress theme and website generation at once.

Flexible Pricing:

• Cursor: Costs $20/mo for individual users and $40 per user/mo for companies.
• GitHub Copilot: Costs $10/mo for individual users and $39 per user/mo for companies.

4. Find Your First Customers

Build a Playground:

• Tabby: Has a playground with a sample coding task.
• Blackbox AI: Has a playground with pre-built coding prompts.
• Codeium: Has a playground with Python, JavaScript, Go, C++, and Java.

Share Sample Problems:

• Sweep: Shares sample coding issues it can solve.
• CodeWP: Shares AI code snippets and plugin examples.
• Bito: Shares AI prompts for generating new code or fixing existing code.

Build in Public:

• Shawn Wang: Building smol.ai in public.
• William Zeng and Kevin Lu: Building Sweep in public.
• Sandeep Pani and Naresh Ramesh: Building Aide in public.

Offer Beta Access:

• smol.ai: Runs a private alpha test.
• Assistiv AI: Opened beta for AskCodi Agents.
• Codebuddy: Runs a closed beta test of its VS Code plugin.
• Tempo: Runs a private alpha of its React UI code generator.

Build a Waiting List:

• CodeComplete: Opened a waiting list for individual developers.
• Durable: Opened a waiting list for its serverless AI code generator.
• JetBrains: Opened a waiting list for its AI assistant in its code editors.