Embracing the New Era of Autonomous Transformation
First in a series to introduce our key investment theses
Hi! Jamie here, Founding Partner @ Scalebridge. Scalebridge is a thesis-driven venture capital firm specialising in automation with a deep interest in legacy industries. We combine foundational investment theses with deep research in the most promising areas across the entire stack within legacy industries.
Autonomous Transformation is a pivotal investment thesis that has been brewing internally for some time, alongside some of our portfolio companies. We're finally pulling back the curtain to outline the concept that underpins the backbone of our investment framework and, in our view, is poised to redefine the next decade of tech landscape.
The Evolution of Digital Transformation
Even in the economically turbulent year of 2024, digital transformation remains a linchpin for corporate IT spend. Companies are channelling significant resources into this area, making it one of the most resilient and expansionary facets of business investment.
Since first coined over a decade ago, the term "digital transformation" has been a beacon for progress. According to IDC, the digital transformation market size reaching a staggering $1.6 trillion in 2022, is forecasted to nearly double to $3.4 trillion by 2026. However, these impressive numbers belie a sobering reality: digital transformation projects have a high failure rate - 70% faltering in reaching anticipated results.
Time to Rethink Digital Transformation Model
The past decade's consultants-driven digital transformation model is becoming obsolete. The rigidity and complexity of earlier generations of tech solutions, coupled with the heavy reliance on external consultancy, have led to digital transformation project failures. Siloed and patchwork solutions, driven by an outside perspective, have often resulted in half-hearted optimisations that lack internal alignment and execution to truly transform organisations.
The Next Chapter: Autonomous Transformation
At Scalebridge, we believe we are on the brink of a new era: Autonomous Transformation, transitioning from consultants-led transformation to automation product-led transformation.
Our Vision for Autonomous Transformation
Autonomous Transformation harnesses data, workflow automation, and AI to achieve strategic goals with minimal manual interference, extricating people from most parts of processes. While humans are mostly out of the loop, they focus on orchestrating and setting strategic goals and boundaries. To align strategic goals, autonomous processes will make real-time independent decisions, recalibrate existing end-to-end processes or create new processes, and action to serve the best possible outcomes.
Opportunities In the First Wave
We’ve observed the convergence of capabilities between services and emerging technologies over the last few years, hastened by challenging economic conditions. We noticed there is an emergence of a cohort of potential future leaders in autonomous transformation. These automation companies extend beyond mere workflow optimisation, to problem-focused automation, packed with data insights, decision-making support, and execution. Ultimately starting to replace traditional digital transformation consultancy and IT services, and leapfrog technology debt, data debt, process debt, and skill debt accumulated over the last 30 years.
While incumbents appear to clock in early wins by embedding AI into their platforms as add-ons, leveraging their distribution advantage, we firmly believe the early-stage automation native startups will be the ones architecting the future of autonomous transformation.
The potential opportunity today is immense, with over $5 trillion spend up for grabs, including $3.6 trillion in digital transformation and $1.5 trillion from outsourced IT services.
Grounding Expectations
We are still in the early innings of the automation cycle, evolving from initial experimentation to full-scale production—a journey that will span over the next decades. For the builders working on Autonomous Transformation solutions, there are some key challenges we observed:
AI is all you need?
Automation: Full stack approach
AI alone—while a potent enabler—is insufficient to drive results. AI is kind of like an engine. It's the driving force behind the whole operation. But just like a car needs more than just an engine to move forward, AI needs other components like workflows, data, UI, and business logic to really make progress.
Adoption: AI hype meets reality
AI is at the peak of the hype cycle. Despite the recent surge of interest in AI, its actual deployment is still minimal.
Accuracy & reliability: Muddy waters
Hallucination and consistency are some of the persistent key issues with LLMs today.
Deterministic execution is critical in automation. LLM usage is still limited at task levels and is not yet used for reliable planning or reasoning.
Deploying human-in-the-loop could help increase adoption, and improve assurance of output quality and accuracy…. well, kinda of.
Agentic automation models show strong promising results (see below), however still early in development.
Data, data, data
Data quality: First thing first
AI performance is only as good as the data it is trained on.
Data connectivity & governance
Bridge siloed structured and unstructured data with efficient governance.
Data moat: Industry specificity
The access to proprietary industry-specific data and deep underlying knowledge of workflows will build a strong moat.
Processes: The good, the bad, and the ugly
Complex enterprise environment
Today, AI still requires clear human guidance to manage evolving, complex and sometimes inexplicit workflows. Take a large multinational for example, its order-to-cash process has 30 million cases and may generate 900,000 different process variants in one year.
No public process data to train on.
What to automate?
Choose the right processes for automation. Automating flawed or outdated processes can amplify those flaws across the entire system.
Reimagine workflows from first principles, not just automate existing ones
Process bottlenecks, inefficiencies, and opportunities for improvement are hard to spot.
We are All-in on Autonomous Transformation Since Day 1
We have already seen a glimpse of the autonomous future through our investments.
Versori, replacing Integration Consultants with an AI-enabled any-to-any data integration no-code platform, automating the entire workflow for enterprises.
Spendkey, AI-powered spend automation platform that has replaced the majority of Cost Optimisation Consultants’ services, bringing analytics, decisioning, and execution capabilities into one place to reduce spend.
Garvis (Acquired by Logility), explainable AI supply chain demand planning copilot platform with a long-term mission of autonomous decision-making, superseding the need for data scientists.
Trusstor: A construction operations platform that automates planning and management through its unified data platform including proprietary zero-intrusive IoT data.
We will delve deeper into autonomous transformation in future posts. At Scalebridge, we partner with builders transforming legacy industries at pre-seed and seed stages. If you are a builder in AI, automation and legacy industries, feel free to DM me on LinkedIn or email me at jamie@scalebridge.capital. I would love to chat with you.