By 2021, seven in 10 enterprises will be using some form of artificial intelligence in the workplace. “Digital workplace leaders will proactively implement AI-based technologies such as virtual assistants or other NLP-based conversational agents and robots to support and augment employees’ tasks and productivity,” said Helen Poitevin, senior research director at Gartner.
Joining the arsenal of AI tools – in fact, already quietly incorporated into a wide variety of enterprise apps and services and acting as advance scouts for AI in the enterprise – is machine learning.
In a modern enterprise landscape, IT professionals aren’t responsible only for systems administration or support with apps and services.They’re now charged with finding ways to help their employers reach their business goals: expanding the company’s top-line growth, optimizing workplace processes while improving employee engagement, increasing customer engagement and retention, and protecting the company from tech-related risks. Machine learning offers tools to advance those goals.The real challenge for IT professionals now is to be able
to deliver a well-informed assessment of machine learning options for their business, then implement them.
This report will cover the following:
- How to Get Your Data Machine Learning-Ready
- Operating System and Hardware Modernization
- Implementation: The Cloud May Be Where the Enterprise Keeps Its Machine Learning
- Is There Ever a Time When Machine Learning Doesn’t Work in the Enterprise?
- Hardware and Software Inventory
- Strategies for Deploying the Rollout
- How Machine Learning Affects Your Industry
