When a provost in higher education wanted to increase enrollment by 5% he turned to artificial intelligence (AI), because it had the potential to significantly impact enrollment numbers.
When a leading telecommunications company went through a global merger, IT turned former rivals into friends by using AI to bridge skills, language and culture gaps across the new company.
When a European trucking company deployed an AI-powered translation interface for drivers and lift operators to communicate across languages, the company benefited by delivering more freight more efficiently.
Despite hailing from different industries and different geographies, all three companies focused their AI efforts on improving critical business priorities. “What matters the most to you and the business is where you should use AI,” said Whit Andrews, Gartner vice president and distinguished analyst, during Gartner Symposium/ITxpo 2017. “If you’re exploring AI for your business, pursue something that is critical to your organization.”
Basics of AI
Common definitions of AI focus on automation and, as a result, often miss the hidden opportunities available to IT and business leaders. AI is technology that emulates human performance typically by learning, and can best be summarized as being able to classify and predict faster and at higher volumes than humans can accomplish without AI.
To deliver business-critical results, organizations apply AI to improve speed and efficiency, improve data processing and analytics, and enhance customer experience. Using these categories as an initial lens through which to view AI opportunities, businesses are focusing efforts on specific use cases that benefit critical priority areas:
Sales and marketing: Customize the sales process, personalize communications to prospects and clients, match sales staff to buyers and offer personalized pricing
Service: Offer virtual customer assistance and triage, predict maintenance and upcoming repair needs, connect service staff to customers and discover process gaps.
Supply chain: Discover and correct data errors, discover risks in the supply chain, elevate insights from IoT devices in the field and plan logistics
Office: Locate and connect to expertise, discover and deflect compliance errors, support meetings and interactions with action items, and enhance digital dexterity With CEO priorities centered around growth and the role that customer experience plays in driving growth, it’s no surprise many companies currently use AI to tackle customer-related initiatives first.
In banking and financial services, chatbots help customers access their bank balance.
In healthcare, virtual nursing assistants follow up with patients post-discharge.
In retail, machine learning and natural language processing learn from customer data to generate behavioral insights.
In education, AI “tutor-bots” provide personalized learning. AI is not confined to business-to-consumer (B2C) models, either. One B2B company operating a distribution center told its partner operating in the same facility it would be installing software into the warehouse to “listen” to operations as a way to spot efficiencies and get ahead of issues.