Guest blog by David Schubmehl, Research Director, Conversational AI and Intelligent Knowledge Discovery, IDC
2020 was a difficult year for most organizations. Due to the pandemic, many organizations faced significant changes to their profit and business models, organizational structures, workforce management, supply chains and many other processes in months, not years. The rate and pace of change has not slowed down even though organizations are embracing the “new normal”. These extraordinary times are forcing companies to rethink their operations and business models, often drastically.
Organizations are looking for ways to transform their business processes to make them more efficient, customer centric, cost-effective and resilient. Increasingly, they are considering artificial intelligence (AI) and machine learning (ML) key drivers of their digital transformation strategy. To thrive in an ever-changing digital economy, enterprises must improve operations and innovate rapidly using technologies like AI and ML. AI automation and analytic tools are becoming the standard for content management, document processing, asset maintenance and customer experience management in the future.
AI and ML are being embedded into applications, making them mainstream within enterprises and resulting in more resilient organizations with improved business performance. Organizations are starting to use these tools to create automated document processing, workflow automation, advanced decision augmentation and a range of other use cases. And organizations are prioritizing technology investments based on how helpful tools are at enabling business continuity and stability. Technologies such as AI and ML will continue to be pushed into focus as they enable digital transformation, automation, improved decision making and business optimization. In fact, IDC predicts a strong compound annual growth rate of over 17% for AI software for the years 2020 through 2024 despite challenging circumstances over the last 12 months.
Despite the range of use cases, IDC believes organizations should align AI deployment to key outcomes covered in OpenText’s recent webinar. AI can empower organizations to rethink the future by reducing costs, automating for efficiency, and reducing risk. For example, organizations can reduce costs by using AI and ML solutions to identify redundant, obsolete and trivial (ROT) data. AI and ML helps automate the time-consuming process of tagging content so that organizations can establish a consistent structure for unstructured content that helps them identify ROT. Enriching content’s metadata using AI helps organizations know what information is key and where it can be accessed. This has several benefits, including reducing data and storage costs through the smart use and implementation of AI combined with data archiving, reducing the number of active data siloes and improving information governance and findability in the organization.
Using AI/ML to automate and reduce the complexity of document related business processes is also a way to reduce an organization’s costs as well as speed up operations. Moving to AI-assisted contract analysis can help to improve business operations while helping to find errors and potential problems that will reduce risk and improve the overall bottom line. Using AI and ML to analyze documents helps to reduce the vulnerability of privacy breaches and other risks by identifying and classifying personally identifiable information (PII) in content to trigger compliance workflows. It also helps to reduce compliance problems and costs associated with compliance by automatically securing and applying policies to PII.
Implementing AI and ML allows enterprises to nimbly adapt to business changes by rapidly transforming information sources into actionable insights. Strong AI & ML platforms such as OpenText™ Magellan™, provide the tools necessary to tackle current organizational needs for automation, improved efficiency and customer experience, costs decrease and risk reduction. The OpenText Magellan platform is also being leveraged in several OpenText solutions where AI and ML can provide improved return on investment and reduction of costs based on better performance and task automation.
Machine learning and AI-powered automation are necessary components of any digital transformation project today. As organizations react and adapt to the ever-changing landscape of business, they need to embrace these tools to save costs, reduce risk, increase revenues, and improve their overall agility.
To learn more about how to rethink the future with artificial intelligence, read the IDC Industry Brief Creating the Resilient Organization Using AI and Text Analytics.
Dave Schubmehl is Research Director for IDC’s Conversational AI and Intelligent Knowledge Discovery research. His research covers information access and artificial intelligence technologies around conversational AI technologies including speech AI and text AI, machine translation, embedded knowledge graph creation, intelligent knowledge discovery, information retrieval, unstructured information representation, knowledge representation, deep learning, machine learning, unified access to structured and unstructured information, chatbots and digital assistants, and rich media search in SaaS, cloud and installed software environments. This research analyzes the trends and dynamics of the Text and Audio AI software markets and the costs, benefits and workflow impacts of solutions that use these technologies.