Data - it doubles in size every two years and by 2020, the data we create will cross the 44 zettabytes mark. By 2025, it is expected to grow to a whopping 175 zettabytes. Enterprises across industries are faced with data explosion, putting pressure on their operations, enterprise systems, and workforce to process, analyze, and monetize large volumes of data.
In particular, publishing and information services industries have witnessed a paradigm shift in the way data is managed, owing to greater high-bandwidth availability and the rapid increase in number of sources supplying legitimate content across multiple channels. They also face intense competition from new-age startups looking to democratize publishing and knowledge aggregation. For them, data explosion implies the online availability of massive volumes of data from which their customers can derive value.
Publishing and information services organizations can deliver customer value by curating contextualized content and mining for actionable insights from both structured and unstructured big data. The traditional operating model in that sector presents an opportunity for disruptive transformation. There is a need to transform incumbent business processes with intelligent tools and technologies. These include semantic searching, natural language processing (NLP), artificial intelligence (AI), and machine learning (ML), that allow the data to be processed by data fabric, by applying cognitive analysis that can enhance the expert user’s experience. Doing that will improve business outcomes, promote customer centricity, and optimize operating costs.
Finding the needle in a haystack
It is a well-known fact that knowledge workers spend close to 30 percent of their time analyzing information for solutions. Actionable insights are derived from similar use cases expert users can relate to and access. Big data is largely unstructured and spread across emails, PDFs, MS Office files, and images, making it difficult to be described or discovered, let alone be used for actionable insights. According to Gartner, 80 percent of organizational data is unstructured.
AI helps with content curation on various topics where human efforts are simply untenable. AI would assist in research and review, segregating factual data from errors, influencing outcomes, and ultimately, helping publishers deliver a hyper-personalized experience to a wider audience. AI will play an active role in augmenting intelligence in products developed by information service providers. They can cater to educationists, financial customers, clinicians in healthcare, legal experts in legal and regulatory scenarios, and business owners for tax implications.
AI will play an active role in augmenting intelligence in products developed by information service providers.
Engaging the consumer
In healthcare, clinical data products support value creation for physicians by enabling comprehensive coverage of a wide range of specialties. These include supporting advanced search for faster response to critical questions, provisioning for updates of evidence-based data almost daily, if not in real-time, ensuring accessibility at point of care, and simplifying personalization and data sharing.
In the legal industry, analysis of legal data by AI can influence legal outcomes, leaving a profound impact on society at large. That, in turn, opens up the Pandora’s box of questions around ethics and bias associated with AI prediction - an aspect that must not be overlooked while embedding AI within business processes.
Linguistics AI is another area of interest because of several high-ROI applications for the industry. Research suggests that nine out of ten buyers in non-Anglophone countries prefer buying products available in their own language. Translation can be manually-intensive and expensive. Using a machine-first translation approach, publishers can optimize their content for a language and augment end-to-end user experience.
It is interesting to note that several publishers are using augmented intelligence as we speak, including Forbes, Bloomberg, and Reuters. In fact, the Associated Press uses AI to automate quarterly earnings reports.
What Next: Publishers and information service providers are experiencing the transformative benefits of intelligent technologies. Enhanced customer experiences and partner relationships, digital scaling, and value creation from content assets improve top and bottom line, increase wallet share in their market segment, and buildenable effective digital transformation of an enterprise.
By forging strategic partnerships with domain-specific technology and service providers, publishers can accelerate digital transformation and adoption of AI and ML. We, at HCLTech, have been working alongside leading companies in the sector to create data fabrics, automate workflows, curate next-generation customer experiences, drive user value creation using NLP and ML for AI-centric predictions, and streamline content development and distribution supply chain.
To learn how we can help you drive exceptional business outcomes, write to us at CS_Marketing@hcl.com.