AI is shaking up the software market, for the better

^{written by José del Barrio and Carmen Sánchez}

Agents and the softwarization of labour

The software industry will have to bring the power of AI to the broader economy and face a collective innovators dilemma in doing so. 

Traditional SaaS solutions were originally designed to simplify specific tasks within job descriptions and boost overall productivity. They serve as tools that augment human work but ultimately require a workforce to operate them.

Take Salesforce, for example: while it streamlines processes for sales teams, businesses still need to hire salespeople to use the platform effectively. This reliance on human labour has led to a historic symbiotic relationship between the software and the labour markets, where both have coexisted separately. B2B SaaS ($230Bn market according to Pitchbook) has drawn from a secularly growing technology budget while operating within job structures funded by a 20x larger payroll budget. 

The adoption of traditional SaaS and Cloud followed a gradual trajectory as the digital rails of businesses solidified and companies gradually grew their technology budget allocation. The business case was built on progressively giving organizations and employees greater leverage. 

However AI is redefining the landscape abruptly. Recent developments in AI are unlocking a new level of automation in software tools driven by its capacity to process structured and unstructured data, understand context and perform in human-like, non-deterministic tasks. The products harnessing this potential are taking the form of AI agents - autonomous software programs capable of executing tasks, making decisions, and interacting with systems or environments. Their ROI proposition is fundamentally different from traditional SaaS: instead of gradually improving efficiency, AI can autonomously execute entire tasks and replace human labor in certain roles. With AI, software tools can not only organize but execute tasks autonomously, becoming capable of completing entire job functions without human intervention. 

Agentic systems have arguably deeper and more sudden implications than previous platform shifts, representing a move away from simply enhancing productivity to replacing humans with AI agents, especially in roles involving highly repetitive and deterministic tasks.

A study by McKinsey already highlights the remarkable speed of AI adoption among businesses. In 2023, large global enterprises spent c. €15 billion on GenAI solutions, which accounts for 2% of the global enterprise software market. It took four years for enterprise spending on SaaS to reach the same market share.

As a result, AI startups are making money at an unprecedented rate, far outpacing previous waves of SaaS companies. According to an analysis by Stripe, top AI companies are reaching millions of dollars in sales within their first year of operation. In fact, AI startups that scaled to +$30 million in annualized revenue did so five times faster than SaaS companies, achieving this milestone in just 20 months. 

‍The transition to Service-as-a-Software era will shake up the foundations of SaaS

When AI-powered SaaS products are positioned as services that replace in-house labor, the internal process changes completely. As existing workflows are no longer relevant, an opportunity arises to replace the system of record and create vulnerability amongst incumbents. This creates an opportunity to replace the system of record.

AI agents are set to become the main players in the emerging agent economy - an era where internal business processes are redesigned, where the SaaS acronym shifts to Service-as-a-Software, and where the term “agent” becomes as commonplace as “website” or “app”. 

Opportunities and challengers for incumbents and challengers

As AI transforms the software landscape, both incumbents and challengers will join the race, each facing distinct opportunities and challenges. Both will benefit from (i) TAM expansion but will need different strategies to navigate (ii) the innovator's dilemma, (iii) distribution power and (iv) product & tech architecture. 

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(i) TAM expansion

AI agents will significantly expand software’s total addressable markets by tapping into the largest budget of all: payroll. Labor and software are merging into one massive market. For perspective, US companies spend over $5 trillion on knowledge workforces, compared to $230 billion on B2B SaaS solutions. 

Beyond TAM growth, AI agents unlock a massive high margin business opportunity by transforming low-margin human services (below 30%) into high-margin SaaS tools (above 80%) across industries and roles. 

However, SaaS has been operating in a near-zero marginal cost model where licenses were inexpensive. Now, AI demands high computational power, turning software usage into a more utility-like paradigm where usage directly correlates with infrastructure and energy costs. As a result, software margins are likely to face downward pressure, as rising computational costs increase COGS (cost of goods sold) and software development becomes increasingly commoditized.

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(ii) Innovators dilemma

The rise of AI agents presents a classic innovator’s dilemma, creating a prime opportunity for challengers to disrupt the market. Startups, free from the constraints of legacy products and established user expectations, can reimagine workflows and business models from the ground up. 

On the flipside, incumbents are shackled by their past. They have to deal with questions that startups do not have to worry about: Is this a good ROI? Do we have conviction that the risk of failure is low? Is this compliant with all our internal policies? This long list of internal hurdles can slow them down.

In this particular case, incumbents will face a significant challenge rethinking their pricing models. Right now, software vendors often monetize through seat-based subscriptions, but as AI agents become capable of executing end-to-end tasks, there will be a shift to outcome-based pricing. This new model allows companies to capture more value by charging for the work completed, directly linking revenue to customer success. The ultimate form of value-based pricing!

While this shift is particularly suited to challengers, it raises questions about incumbents' ability to adapt. How will they manage legacy pricing structures while integrating new AI-driven offerings? For instance, Salesforce currently charges per salespeople seat for its platform. Will it be able to transition to a charging per successful sale?

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(iii) Distribution power

Incumbents hold a clear advantage when it comes to distribution power. With minimal product-market fit, they can secure distribution effortlessly, thanks to their established customer bases, vast data resources, distribution channels, brand recognition and partnerships within the ecosystem. As usual, the battle will ultimately come to whether the startup gets distribution before the incumbent gets innovation. 

However, past tech revolutions (such as personal computers, cloud or mobile) have shown that incumbents often struggle to ride the next wave of innovation. Very few companies were able to adapt. This raises the question: will today’s incumbents - or even startups that aren’t AI-native - be able to compete effectively with AI-native challengers? It’s possible that only those built from the ground up with AI at their core will thrive in this rapidly changing landscape.

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(iv) Product and tech architecture

In the product and tech arena, startups will be able to build AI-native architectures from scratch, sidestepping the technical debt that incumbents must navigate. This clean-slate starting point will allow challengers to take bold technological bets and design systems optimized for AI capabilities earlier.  As Vijay Pande notes, "AI-first companies have the advantage of designing their entire stack around AI capabilities."

On top of that, the rapidly evolving nature of AI technology will favour those who can develop modular and adaptable architectures, allowing for quick integrations of new advancements. This flexibility gives challengers an edge in a fast-paced environment where velocity defies gravity and staying ahead of the curve is essential. 

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Who is joining the race?

There are already some SaaS companies capitalizing on the agent economy opportunity, reshaping entire business processes and challenging the system of record, particularly in roles where the value of hiring AI clearly outperforms the value of hiring labour. This transition is starting with simpler jobs - those involving repetitive, time-consuming, and high-volume tasks - and will gradually extend to more complex roles as AI capabilities advance. 

An interesting opportunity will likely arise in the app layer. Both the cloud and mobile transition generated around 20 application layer companies doing over $1Bn in revenue. The space remains white for AI-native app-based companies. 

As we stand on the brink of this transformative era, it is clear that the emergence of AI agents will redefine the landscape of work and innovation. At Samaipata we are committed to support the disruptors who dare to better the world.

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