As machine analytics improve and artificial intelligence begins to automate basic routine processes, businesses have begun automating work that was traditionally completed by humans. The rise of artificial intelligence is a function of two variables that predated it: quantity of data and analytics processing. The creation of technical architectures to capture and process large quantities of data (“big data”) shifted companies forward as they grappled with the complexity and quantity available; as a result, many were unable to draw insights. The explosion of analytics processing (machine learning, deep learning, heuristics) and analysis of the resulting information move the world forward once again.
If properly organized data creates information, and properly organized information creates knowledge, then the application of that knowledge to a specific use case (i.e. a customer’s facts) can create intelligence. It is this merging of big data and analytics that is fueling the artificial intelligence boom we see today.
The Commercial Implications of Intelligence
The Intelligence ecosystem is beginning to build steam. Articles from prominent venture capitalists like Jerry Chen in “The New Moats” (pointing to “Systems of Intelligence” being the “Next Defensible Business Model”) and Phillip Stauffer in “Dawn of the Ultimate Unfair Competitive Advantage” (“data and intelligence is the ultimate unfair competitive advantage for at least the coming 10 years”) describe the commercial implications of intelligence. Businesses will transform what was the traditional arena of service workers into “streams” of information. Similar to market data, or even television content, each is an ongoing stream of information presented in real-time, targeted to a specific customer.
While the key to creating intelligence includes merging domain expertise with technology, the downstream impact is still the same: firms must focus their sales and execution strategies on players in the market who would benefit from increased automation. Larger customers are typically the first adopters, followed-by cost-conscious middle-market competitors and then mass adoption. However, this need not be the case: because of the targeted nature of the offering, systems offering domain-specific intelligence will be available to customers of all sizes.
The outstanding question, then, is how to deliver this “intelligence” stream in an effective way for customers? The answer is “Intelligence-as-a-Service”, or IntaaS.
What is Intelligence as a Service?
Intelligence-as-a-Service* is the combination of automated domain expertise (using machine learning, analytics, and artificial intelligence) with traditional SaaS delivery platforms. Imagine if your CRM came pre-filled with customer information, or your taxes were pre-loaded and completed in your tax software: this is the promise of IntaaS. Software-as-a-Service reduced the marginal cost of delivering a unit to a customer to near zero. IntaaS reduces the marginal cost of both creating and delivering a unit to a customer to near zero.
Ascent’s Use Case
The distinction between businesses that utilize a standardized application of deep-learning models and our approach is centered on the variability of data. In systems where the inputs are consistent and standard, and the output is identical (think self-driving cars), deep learning works extraordinarily well. Even in those systems, miniscule failure rates are extraordinarily risky. In systems where the inputs are dynamic and the outputs are targeted (n=1), deep learning must be supplemented by domain expertise and domain-specific technology (think regulation and law).
This is what we have done at Ascent. By combining our knowledge of regulation and rules with data science and technology, we built automated processes that allow us to (1) create regulatory intelligence channels and (2) feed those streams through our SaaS delivery platform. Users have the ability to access a variety of regulatory channels and construct a custom regulatory ecosystem for their firm. The results are remarkable.
We can build intelligent regulatory processes in seconds, produce compliance manuals in a moment’s notice, and create compliance reports that used to take months in a matter of minutes. This is the power of Intelligence-as-a-Service: it will act as a digital backbone for any firm – at any time, from any place – with consistent, accurate information. It will allow humans to concentrate on unique and bespoke tasks, rather than organizational efficiency, unlocking employee creativity and encouraging problem-solving that computers are (as of now) unable to solve.