Artificial intelligence (AI) and machine learning are two buzzwords in today’s IT vernacular, and for good reason. Many organizations have already leveraged these advanced analytics to solve real-world problems, with great results and return on investment. However, the scope of these deployments are often artificially narrow and don’t take full advantage of the capabilities available. As IT executives build out their long-term strategies, it will become increasingly important to look at this technology more holistically — to drive further insights and efficiencies to fuel their digital transformation initiatives. Here are some use cases to illustrate the breadth of the analytics everywhere opportunity:

Boost and sustain revenue

Perhaps the most talked-about use case, big data analytics have become a technology imperative to augmenting the top line. New ways to bridge formerly distinct data silos now enable organizations to finally bring analytics to the data. As a result, organizations are more successful in deriving accurate and actionable insights to outpace competitors by acting on unmet customer needs, underfunded parts of the business, emerging business models and more.

Drive customer engagement

Organizations are constantly looking for new and better ways to engage customers at a reasonable cost, and analytics play a critical role in this endeavor. Possibilities include eliminating intermediaries and employing digital platforms to reach and serve customers directly, closing the loop between data and action, and truly understanding customers to better satisfy their needs. Around 70 percent of customer engagements will be driven by intelligent systems by 2022, according to Forrester Research, which will largely be driven by cognitive search and chatbot technology.

Streamline and enhance processes

Today, the internet of things (IoT) is creating massive volumes of sensor data with untapped value. By applying IoT analytics at scale, organizations can reduce service costs, improve customer satisfaction and create entirely new business models. For instance, IoT analytics deliver on the promise of predictive maintenance, smart metering, intelligent manufacturing and more. Operations analytics ensure automated IT monitoring and remediation to reduce mean time to repair (MTTR) and operations costs. Legal departments even use predictive coding, or technology-assisted review, to improve and streamline the process of reviewing data for legal matters, which typically drives greater speed and accuracy.

Protect citizen privacy

When the General Data Protection Regulation (GDPR) became effective in May 2018 to protect the European Union nations’ citizen data, many other countries and jurisdictions followed suit to protect their citizens’ data as well. Analytics yet again come into play in this compliance use case, as the sheer volume of information to protect requires a new level of intelligent classification. Organizations do not have to protect all their data — nor do they have the budget or infrastructure to do so — but instead, just the right information. File analytics and structured data management technologies play a critical role in protecting organizations from fines, sanctions, lawsuits and erosion of market credibility.

Detect and prevent risk

Security operations and global security operations centers can leverage analytics to automate the examination of vast amounts of data and ensure that teams investigate real threats instead of testing hypotheses or chasing false alerts. When looking for insider threats, for example, user and entity behavior analytics (UEBA) hone in on user information — abnormal logins, time of work, etc. — to identify difficult-to-find threats. Analytics even deliver real-time threat intelligence, or physical security, by scrutinizing video and audio from CCTV, social media and sensors.

The multifaceted role that AI and machine learning can play in digital transformation is likely why more than 50 percent of organizations are planning to leverage advanced analytics in the next 12 months, according to an IDG study. Just be sure you draw the circle big enough on objectives to derive the greatest possible value from your initiatives.