Automate repetitive processes and offload manual tasks so employees can focus on more strategic endeavors with AI automation. Robotic process automation can handle tasks like completing forms and moving files. AIOps augments IT staff’s operations and infrastructure efforts with scalable automation. It is especially useful when the data sets are so large that humans can’t detect potential issues and determine their root causes.

Benefit from guidance and direction on using AI tools like Microsoft 365 Copilot, OpenAI GPT-4 and Google Bard from a trusted advisor on incorporating the latest technologies into your organization.

Deliver more value and a superior user experience at less cost by letting chatbots and virtual assistants respond to customer queries for help desk and end-user support services. Human-to-machine interfaces are built on how humans interact with laptops, computers, cars and other devices for a user-friendly experience.

Research the performance of your content using machine learning and AI, including capabilities like text analytics, data quality analysis and case management, so your marketers can more easily and effectively manage, measure and improve content.

Speed the development, testing and release of software applications, configuration changes, bug fixes and new features using advanced analytics and an AI core foundation.

Understand your customers deeply with customer analytics, segmentation and competitive intelligence so you can predict their future needs, personalize your messaging accordingly and stand out from competitors.

Build predictive models for specific industry needs by harnessing human expertise and machine learning (ML) algorithms. Banks, for example, can build models to help predict and prevent credit card fraud.

Leverage data generated by IoT devices using location-aware software tools. Banks or retail businesses, for example, can tailor service for customers using insights collected from IoT sensors, beacons and mobile apps.

Eliminate downtime and equipment failure with AI-led health monitoring of industrial equipment and technology to catch issues that could become problems if not addressed. Predicting and responding to IT failures faster leads to greater business resilience.

Access subject matter experts and machine learning algorithms to build predictive models for specific industry needs. Potential uses include: predictive endpoint health using benchmarked data to reduce reactive user incidents; self-learning automation optimization to analyze chat transcriptions and add feedback; and mapping of business personas using clustered pattern detection.

Arguably the most complex use of AI, prediction and reasoning involves humanizing the software and machine so it can forecast and interpret data for people. Applications include more accurate and precise forecasting of tornados and other severe weather events. Airlines can build models to analyze passenger flows at airports or improve flight connections.

Predict cybersecurity threats by detecting anomalies in user behavior and finding threat vulnerabilities. Unisys received funding from the Artificial Intelligence for Decision Making Initiative in Australia – a collaboration between the Office of National Intelligence and the Department of Defense – to investigate using forensic data analysis to detect deceitful and persuasive writing.

Track and measure pay equity to find workplace inequities using software algorithms and machine learning and reduce biases related to recruiting, resume screening and upskilling