Accenture launched its Applied Intelligence Platform to make it easier for clients to transform the enterprise through artificial intelligence (AI). The new platform allows organizations to apply pre-configured self-learning industry solutions, as well as develop new solutions, without the need for deep data science expertise — which is becoming an increasingly scarce resource.
Applied Intelligence Platform builds on the Accenture Insight Platform through which Accenture has been offering analytics applications using machine learning and deep learning to clients. It will integrate these capabilities with edge analytics and Internet of Things (IoT) services, as well as access to more than 350 data sources — all made accessible via an on-demand, low-code platform. As a result, clients are less dependent on specific technologies as the platform leverages solutions and tools from leading technology providers, to enable creation of the proper solutions across industries and functions.
“The Applied Intelligence Platform enables AI-powered transformation at scale as clients will be able to systematically embed AI across their operations — from the edge right through to the cloud,” said Mike Sutcliff, group chief executive, Accenture Digital. “Thanks to the platform, the power to leverage AI to drive unprecedented new growth and efficiencies and unlock new insights, business models and experiences is within reach of every organization.”
Applied Intelligence Platform can deliver numerous benefits to clients including:
- Scaling impact not investment. The platforms pre-configured services won’t require clients to build and maintain costly custom infrastructure and services from scratch.
- Increased speed and agility. The platform uses open, standards-based platform services, APIs, and tools, which clients can use to rapidly build and move from prototype to production.
- Chance for new growth opportunities. The Applied Intelligence Platform ecosystem fosters intelligent applications that run models on continuously updated enterprise and device data, which can drive network effects and new business models.
- Edge analytics and IoT integration. The platform allows businesses to run machine learning and deep learning applications at the edge, and also better source data from IoT devices to power real-time applications and automated processes — enhancing efficiency and providing more data to fuel operational insights.
- Enhanced security. Recommended, end-to-end security and privacy services are enhanced through the localization of sensitive data processing at the edge.
Accenture, with its team of industry specialists and more than 3,000 data scientists, has already developed a range of use cases and more than 40 intelligent industry solutions for Applied Intelligence Platform to help bridge the gap between information technology and operational technology. Use cases include asset and fleet management solutions expected to unlock efficiencies across manufacturing, transportation and logistics, and energy. Examples from the platform’s suite of intelligent industry solutions include:
- Remote monitoring — a global asset monitoring solution based on device data from installed industrial equipment. It is designed to reduce warranty repair costs through diagnostics to calculate mean-time before failure, as well as enhance equipment knowledge and supply chain efficiencies for spare parts.
- Fleet management — an IoT-enabled telematics solution to improve operational efficiencies and reduce cost with embedded analytics and AI. It provides fleet operators better insights including vehicle tracking, diagnostics, critical event alerts, driver behavior monitoring, reporting, and route management.
“Data science to date has largely been decoupled from operations and application development, and models are often created and deployed only to be orphaned as there is a limited feedback on their effectiveness,” said Athina Kanioura, chief analytics officer and global lead of Accenture Applied Intelligence. “Our new Applied Intelligence Platform provides non-data scientist with the tools and access to the data they need to rapidly assemble and apply applications while the platform ensures the effectiveness of the underlying advanced analytics.”
