As Artificial Intelligence evolves from a groundbreaking concept to a tangible asset in day-to-day business operations, revolutionizing the internal processes within organizations is becoming increasingly feasible. At ClearContract, we recognize tremendous potential in productizing internal responsibilities—beyond the external professional services like legal or accounting. Internal operations, often underappreciated but essential, include everything from data entry to routine procedural tasks that keep organizations running smoothly.
These operational duties often consist of repetitive and mundane activities that warrants streamlining. Traditionally, companies have tried to address this need through Robotic Process Automation (RPA). However, with advancements in generative AI, and our development of an AI-based Copilot for Microsoft Word, we now see an opportunity for true automation that surpasses initial RPA capabilities. Companies such as Decagon with automated customer support and others using innovative tools from entities like Anthropic are just the glimpse of a new era where productivity tools can now integratively function with existing software suites in intelligent ways.
This prefaces a future where AI agents, like ClearContract’s Copilot, can genuinely realize the automated efficiencies once promised by RPA, allowing personnel to direct their efforts toward more strategic, impactful tasks.
Reimagining RPA with AI
Operational tasks encompass a broad spectrum – from data entry and document review to complex information migrations and web interactions. Despite a digital world, many processes still rely on outdated methods such as spreadsheets and paper forms. Although RPA emerged as a promising solution, with pioneers like UiPath claiming to craft an “automated enterprise,” the technology fell short of delivering true automation due to its rigidity and high implementation costs.
These systems were built to replicate human actions by “programming” keystrokes and mouse clicks, which required businesses to hire pricey consultants. As a result, RPA remained largely inaccessible to smaller companies. However, with the advent of large language models (LLMs), this vision is finally viable. Instead of programming each specific action, AI agents, like our Copilot, can receive a clear target—like scheduling meetings or extracting data—and be equipped with the necessary tools and understanding to autonomously perform these tasks, adapting flexibly to changing inputs and business processes.
The Expanding Horizon of AI in Operations
The enormous market potential for intelligent automation excites us at ClearContract for a couple of reasons:
Firstly, the scope is vast. There is a multitude of operational tasks that current technologies do not address, tasks still done manually despite advancements in digital practices. From streamlining operations for more than 8 million clerical roles to tapping into the $250 billion Business Process Outsourcing industry, intelligent automation holds immense promise for reshaping labor costs and efficiency.
Secondly, a significant opportunity exists for startups to lead this domain. Many of these workflows haven’t been productized into existing software due to their bespoke nature. Unlike established “systems of record” like Salesforce or Workday, this field has open terrain for innovation and integration of AI without needing legacy systems.
The market opportunity presents itself primarily in two domains: horizontal AI solutions catering to various industries, and specialized vertical automation solutions focused on end-to-end workflows for specific sectors.
Mapping the Intelligent Automation Landscape
Horizontal AI Solutions
Many intelligent automation firms are developing similar internal capabilities, presenting opportunities for specialization. ClearContract, for example, focuses on enhancing legal document workflows, transforming unstructured data into actionable insights. Companies like Reducto are pursuing similar horizontal solutions to solve unstructured data handling, but in their distinct focus areas.
There are multiple foundational components vital for sophisticated automation—creating web data scrapers, structuring data streams, and facilitating legacy system updates among them.
Vertical Automation Solutions
We see substantial merit in developing vertical solutions—that is, software specifically tailored for distinct sectors. This approach allows AI agents to provide precise performance and integration levels necessary for customer satisfaction. Using LLMs, industries such as healthcare and logistics have begun revolutionizing specific operations.
For instance, in the healthcare industry, intelligent automation is streamlining referral processes, cutting down manual entry requirements and accelerating new business acquisition. In logistics, AI-driven tools are optimizing load management and order processing, enhancing efficiency and accuracy without necessitating large-scale system overhauls.
These strategies focus on crucial workflows, positioning startups as essential resources for their clients due to integration from the outset. This “land and expand” model is proving successful for intelligent automation firms.
In Conclusion
At ClearContract, we are enthusiastic about the direction intelligent automation is heading. LLMs are allowing us to revisit and potentially fulfill the unfulfilled promises of early RPA systems by transforming traditionally labor-intensive tasks into automated processes. This opens opportunities in previously untapped markets, inviting new ventures alongside established giants in both horizontal and vertical realms.
If you’re exploring intelligent automation’s potentials and opportunities, ClearContract is eager to engage in conversation. The future is ripe with possibilities for crafting AI-driven tools that revolutionize operational efficiency across industries.
