Other parts of this series:
As I explained in my previous post, at Accenture, we view artificial intelligence (AI) as a capital–labor hybrid that does not degrade over time. In this post, I will continue with a look at how AI creates value, and how it is already used by organizations today.
The promise of AI rests on five levers that create value. Each lever delivers specific and tangible benefits to the enterprise:
Cognitive capabilities on top of automation technologies with self-learning, autonomous, reactive and proactive capabilities.
Results drive enhanced profitability through more efficient processes, activities and services.
Leverage AI capabilities to augment human intelligence on core human-driven processes.
Enable growth by improving quality and effectiveness of human decision making
Deliver superior experience to customers and users based on hyperpersonalization and curation of real-time information.
Drives growth in customer acquisition, retention and overall satisfaction.
AI is enabling a new class of products and services—applying AI into new and innovative products, services, and new business models.
Accelerate growth by introducing new products and services with speed and quality.
Build trust within the organization through the use of AI (e.g., compliance, transparency) and how AI is used.
Enables lower costs to govern and oversee the organization.
Drives organization trust and limits disruption and costs from AI implementation.
Here are some example use cases:
- Mastercard Labs uses Kasisto, a financial services AI platform, to support more “natural” interactions within a messaging app. Specifically, the company is developing Mastercard KAI (text-based AI) for messaging platforms such as Facebook Messenger.
- Amelia by IPSoft is a cognitive agent that can cover a wide variety of service desk roles and transform the customer experience through the use of natural language in applications. For example, it can help customers open new bank accounts.
- Allstate Insurance has deployed Abie, a virtual assistant, to help walk agents through the quoting process for complex products. The context-aware technology understands agents’ inputs and is able to direct them through the process without using the call center.
- For Credit Suisse, Narrative Science’s Quill has helped to summarize information by scaling investment research with natural language generation (NLG). This AI technology has enabled people to augment human intelligence with consistent and comprehensive research summaries.
- DBS Group Holdings uses Kasisto to answer financial and banking queries in its digibank. They have found that Kasisto is able to answer 95% of queries.
- AIG partnered with Human Condition Safety to deploy devices that couple wearable technology with AI and build information modelling. Human Condition Safety is creating tools that help workers, managers and worksite owners prevent injuries before they happen. It is being offered in industries that hold the highest risk for workers.
- Liberty Mutual performs underwriting risk analysis using signal monitoring.
- Blend Labs is accommodating complex rules and regulations changes in its mortgage loans process with intelligent and automatic compliance features.
- Swiss Reinsurance Co. is working with IBM’s Watson to develop a range of underwriting solutions and achieve more accurate risk pricing. Cognitive computing helps them leverage unstructured information around risk to make better informed decisions.
- A major government-sponsored enterprise (GSE) started an automation journey to create a virtual workforce that will increase efficiency, controls, and client-centricity. About 25 processes were identified as candidates for automation.
For more examples of how AI is already used today, I suggest this interesting blog post from my colleague Nicola Morini Bianzino.