AI will give enterprise software the power to eat services: Vista Equity CEO, Robert Smith

Key Concepts

Generative AI (GenAI): A type of artificial intelligence that can create new content, such as text, images, or code.
Agentic Solutions: AI systems designed to act autonomously to perform tasks and achieve goals, often within existing workflows.
Enterprise Software: Software applications designed for use by organizations, rather than individual consumers.
Value of Incumbency: The advantage held by established companies with existing customer bases, data, and workflows.
Total Addressable Market (TAM): The total market demand for a product or service.
Economic Rent: Profit earned in excess of what is required to keep a factor of production in its current use.
Infrastructure: The underlying hardware, software, and networks that support AI development and deployment.
Inference: The process of using a trained AI model to make predictions or generate outputs.
Whole Brain Skills: A combination of analytical and creative thinking, emphasizing critical thinking, problem-solving, and emotional intelligence.
Diversity, Equity, and Inclusion (DEI): Policies and practices aimed at fostering a diverse workforce and equitable opportunities.

AI and the Workforce: Productivity and Restructuring

Robert F. Smith addresses the Financial Times report about Vista potentially cutting its workforce by a third due to AI. He clarifies that while the reported figure is inaccurate, GenAI and Agentic Solutions are indeed driving massive productivity gains. Vista has a history of embracing technological change, having navigated waves of digitization, IoT, mobile, and cloud. Now, AI is the latest transformative technology.

Smith emphasizes that these AI advancements lead to significant productivity increases across various functions, including product development, customer service, and go-to-market strategies. He states, "We are built for growth as a firm. We're going to continue to grow. What's interesting is as you grow you can actually grow without adding as many people." This implies a shift in how workforce expansion occurs, focusing on efficiency rather than linear headcount growth.

He acknowledges that certain job categories will be significantly impacted by AI, while others will be enhanced. This necessitates a "balance of expression and expansion" as these systems scale. Vista has established an "agentic factory" to develop agentic solutions that integrate with enterprise software and unique datasets, creating highly efficient workflows. Smith highlights the "value of incumbency" for enterprise software companies, as their existing workflows and data provide a strong foundation for these AI solutions.

The Three States of Enterprise Software in the Age of AI

Smith outlines three potential states for enterprise software companies in the AI era:

Agentic Rule of 70: Companies that successfully integrate AI and agentic capabilities to achieve significant growth and market expansion. These businesses have a "right to exist" and thrive.
Right to Exist (Incumbency and Data Sovereignty): Companies that possess "sovereignty and dominion over workflows and data sets" that are unique and not widely captured in foundational AI models. Their incumbency and ability to build agentic solutions around these proprietary workflows grant them a right to exist and potentially expand their TAM.
Rule of 60/70 (Cost Reduction and Margin Improvement): Companies that may not have proprietary data or workflows but can leverage GenAI to dramatically lower their cost of delivery, development, customer support, and go-to-market efforts. This allows them to increase profit margins and return capital to investors, even if they don't experience massive growth.

Smith notes that public investors are still trying to discern these distinctions, which is why the market is still sorting out valuations.

AI Infrastructure, Valuation, and Power Constraints

Regarding the valuation of publicly traded AI companies, Smith draws parallels to historical infrastructure build-outs, such as the fiber optic cable era. He states, "It took massive amounts of capital to build out the infrastructure that we benefit from now." While some companies in those earlier waves failed, others succeeded by building at the right time and capacity.

He identifies several factors influencing the AI infrastructure build-out:

Capital Investment: Trillions of dollars are being invested in AI infrastructure.
Power Availability: A significant question is whether there is enough power to support the demands of AI data centers. Smith notes that some argue this is a potential bubble.
Component Parts: The availability and capability of necessary hardware components are crucial.
Distribution: Ensuring efficient distribution of these components and infrastructure.
Power Efficiency of Solutions: Emerging solutions offer significantly lower power consumption, which could alter infrastructure requirements.

Smith believes that power will be a main constraint on AI build-out in the short term in the US, though other parts of the world may have excess power. However, accessibility, latency requirements, and model size for specific use cases are also critical considerations. He emphasizes that not all applications require massive Large Language Models (LLMs); smaller models can be sufficient for certain industry needs.

Investing in Enterprise Software and Market Dynamics

Smith expresses strong optimism about investing in enterprise software, stating, "I am just really excited. I've never been more excited about investing in enterprise software than I am today." He believes that agentic and AI-enabled enterprise software businesses will create massive upside and opportunity for investors.

He notes that while some publicly traded enterprise software companies have been "hammered" this year, this is partly because investors are still trying to understand how GenAI will augment rather than replace existing functionalities. Vista has successfully returned over $12 billion in the past year, with exits primarily through strategic and financial buyers, not IPOs. However, with the IPO market opening, they have companies in registration and are optimistic about future prospects.

Skills for the Future Workforce: The "Whole Brain" Approach

Addressing the challenges faced by Gen Z and Gen Alpha in the job market, Smith advocates for a "whole brain" skill set. He explains that while his generation could focus on STEM and data processing, the advent of AI agents that can perform these tasks more efficiently requires a new approach.

The future workforce needs to combine analytical skills with:

Creativity: Generating new ideas and solutions.
Thoughtfulness: Deep consideration of problems and contexts.
Ecosystem Understanding: Comprehending the interconnectedness of systems.
Emotional Intelligence (EQ): Understanding and managing emotions, building relationships, and effective engagement.

Smith uses the example of sales professionals, noting that they spend only about 15% of their time selling, with the rest dedicated to administrative tasks. Agentic solutions can automate these tasks, freeing up salespeople to focus on the "human aspects of what is it that that solves the problem, the relationship that they need." This shift will lead to a shakeout in entry-level sales prep roles but will enable salespeople to be more effective and handle a larger volume of opportunities.

The Enduring Business Case for DEI

Despite a backlash against DEI policies, Smith firmly believes the business case for Diversity, Equity, and Inclusion remains strong. He states, "The business case hasn't changed. It is you know everyone knows the more diverse thought that you have the lower risk the higher returns the data is all out there now."

He urges his teams to continue hiring the best people and enabling them to be effective. In the US, he emphasizes the need to "actualize as many people as possible using the tools that are available so that we can be the most productive workforce." This is crucial for competing globally, especially as digital capabilities are now accessible everywhere.

Vista is actively involved in equipping students with AI skills through partnerships with HBCUs (like Morehouse and Spelman) and organizations like Code.org, aiming to reach over 5 million students with AI-centric coding education. The goal is to prepare K-12 and higher education students for the new paradigm of work, encouraging them to become masters of AI utilization and to leverage their unique insights as entrepreneurs.

The Importance of People and Alliedship for Racial Equity

Reflecting on his book, which highlights speeches by Dr. Martin Luther King Jr., Smith discusses the current state of racial equity in America. He believes the greatest asset the country has is its people and that "we need to enable and actualize our people." This requires building stronger alliedship around areas needing address.

While he sees progress in some communities, he acknowledges that others are moving backward. He stresses the need to "create enough of a momentum moving forward because moving backward is not going to be an option." The global economy has flattened, and access to technology is widespread. Therefore, the US must ensure every able-bodied American can participate, create GDP, and expand job opportunities to maintain its competitive edge and prosperity.

Rejuvenation and Perspective

When asked about how he recharges, Smith emphasizes connecting with people he cares about, listening to great music, and hearing the thoughts of the youth. He recently enjoyed a trip with his son, involving fishing and roller coasters. He finds perspective by listening to music, particularly John Batiste, whom he considers "the greatest musician of his generation." Planning fly fishing trips with his children is also a key part of his rejuvenation.