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For all the potential of best-of-breed business ecosystems (e.g. SAP, Salesforce, Workday, Service Now, Microsoft 365), companies’ use of them has created new information silos. At the same time, a whole host of potentially useful information remains buried in emails and beyond. Where process automation exists, meanwhile, this is only partial - and generally lacks any contextual understanding.
Small wonder, then, that despite investing heavily in the latest technology many companies are not seeing the returns, while huge numbers of knowledge workers continue to manually consolidate information from a raft of different systems to do their jobs.
The solution to all of this involves bringing unstructured data into the light, and linking associated insights with existing structured data, to create a 360-degree evolving narrative which can serve as the basis for more context-aware process automation.
Context is everything
Future platforms or systems will employ human-like understanding and contextual memory of what that information is, what it means, how it adds to the story. They’ll also ‘know’ how that knowledge might be applied in smarter ways across different use cases; expedite next courses of action; and deliver all kinds of business benefits.
Let’s take invoice and financial management. There is considerable scope here to harness the optimum combination of AI-enabled tools, to make lighter work of this admin-heavy workload. Both in ‘reading’ and making sense of incoming documents; and in intelligently triggering next actions - in the context of wider enterprise services like ERP, CRM, contract management, etc.
Pattern-matching AI, such as deep learning, is ideal for ingesting and processing invoices automatically to identify the type of document and its constituent parts, for instance. Complementing this is a novel form of AI, known as ‘contextual AI’, which can record content in context, e.g. by recalling how a particular kind of document is ordinarily handled (rather like a human’s contextual memory).
Bridging system boundaries
Before companies can harness AI to full effect, however, they must be able to overcome content silos. If the organisation’s knowledge straddles multiple software ecosystems, teams will find it difficult to view and address a situation or opportunity fully.
Integration, at not just a data level – but at a content and process level, alleviates this problem – sharing entities such as customers and suppliers across different systems and being able to automate a process based on these entities.
With today’s speed of change, rather than develop their own custom apps on an enterprise content management system, a more efficient alternative is to ‘snap together’ pre-built but configurable content apps which have next-generation content management capabilities ‘inside’. Under the covers, these content apps can communicate and ‘share wisdom’ based on contextual AI derived from their growing repository, accelerating workflow and business outcomes.
This approach offers companies the best of both worlds. Each specialist solution continues to do its given task well, while also contributing to the broader enterprise knowledge - enriching the 360-degree view of a customer, supplier, patient or business opportunity.
More than a sum of its parts: intelligent content automation
It's this vision – of delivering more tangible impact and timely ROI at a functional level, while contributing to a shared higher purpose – that is driving the convergence of a number of adjacent technology fields. These include ECM for managing content, robotic process automation (RPA) and business process management (BPM) for orchestrating processes, intelligent document processing for understanding incoming content, and enterprise content integration for bridging the content silos and content automation applications.
Together, these developments enable intelligent content automation (ICA) - the next, more intelligent generation of content and process automation which combines content management, process automation and AI-powered document understanding. As all kinds of organisations become more ambitious in their process automation and content management plans, and look to drive next-level ROI from their latest tech investments, cross-enterprise knowledge integration and contextualisation will become increasingly critical.