How AI will help to shape the new normal
None of us is quite sure what the world will look like as we ease back into the new normal. However, AI will become increasingly important permeating every aspect of our lives and the business world.
AI has been evolving quickly, and many believe that the pandemic has sped up its evolution. Organizations are already looking at transforming their processes, people and data optimization to harness the power of AI. Sales, for example, has been hit during the virus. AI can help to identify which customers will buy specific products and make predictions about changing purchasing behaviors.
Despite the benefits AI offers in helping organizations to get back on track after the virus and boost their business, many are still finding it a challenge to exploit the benefits of AI in real-world scenarios.
AI is capable of delivering enormous value in terms of increased productivity, performance and, in turn, profitability. However, an inadequate infrastructure, limited in-house talent and the lack of clean, relevant, easily accessible and organized data is holding many back. In truth, the issue is that AI requires investment to produce return.
Combining learning and rule-based methods in AI
The conundrum here is that most organizations don’t have huge data pools. AI depends on strong digital foundations and clean data to train on. There are no easy workarounds. It is little surprise, therefore, that deep learning systems are not top of the enterprise agenda. Organizations should not be put off by this. They need to realize that algorithms can actually be utilized to pull out meaningful conclusion from small data sets.
There are many examples of the power AI holds in the so called touchless economy. Many retail websites, for example, are introducing AI chatbots to help customers get the relevant information they need 24/7. On the ECM front, AI makes it much easier to pull together data and underscore actionable conclusions that can help to bolster the bottom line. It can also automate repetitive tasks so that employees can concentrate on more high goal projects. It can also provide real time insight into customers and how they view products and brands.
Collecting valuable insight from unstructured content
It is often estimated that unstructured data represents around 80% plus of an organization‘s data. This data is made up of text documents, emails, video, voice recordings, social media and so forth.
Unstructured data is a rich minefield of opportunity, but was more often than not seen as too complex to mine. Cognitive services, content analytics and natural language processing, however, have changed this. This has resulted in some very powerful tools.
Take sentiment analysis, also referred to as opinion mining, for example. It is basically the interpretation and classification of emotions using AI on text data. These emotions can be positive, negative or neutral.
Sentiment analysis provides organizations with unprecedented insight into the way its customers think. It enables organizations to get an accurate picture of customer feelings towards its products, brands or services, for example. This makes it much easier to tailor products and services to customers’ needs.
Intent analysis steps insight up a gear. It is designed to help analyze a user’s intention behind a message, be it email, social media or online chat. This type of information is invaluable in tracking a customer’s buying intent, particularly on big ticket items, and understanding what is necessary to close a deal.
Named entity recognition (NER) is another area where AI can be an impressive and compelling tool. NER addresses information extraction. Its main objective is to locate and classify named entities in text into predefined categories. These can range from names and organizations to values and locations. NER can be used to speed up customer response times by categorizing complaints and filtering them by key words, for example.
Melding information and process management with AI
Many of the ways of getting insight from data work beautifully with structured data or images, but can be thrown off balance when used with unstructured data. To get the best results from AI structured data must be melded with unstructured data. But to do this it must be prepared and useable. The problem is that much of this unstructured data is stored in silos, which makes the task both highly complex and time consuming. This is why AI needs to be combined with information and process management from the beginning.
An ECM solution can correlate data from a host of sources, be they databases, servers, customer relationship management (CRM) tools or file directories. This puts a stop to redundant data storage and puts efficient ordering in place through versioning and metadata. Integrating cognitive services into the platform automatically makes AI available for all applications.
ECM also provides a context sensitive system, capable of managing, storing and scaling data horizontally, that meets the dietary data expectations of AI.
Breaking down the barrier that sits between content and data
The pandemic has changed the way businesses work forever. Contactless business will become a fixture of the new normal. AI has a huge role to play in all sectors of industry, from manufacturing automation to improving contactless personalized customer care.
To achieve its potential, however, there is no escaping the fact that AI must have accurate, clean, and managed data. ECM is AI’s perfect match here in helping organizations establish a safe and successful future going forward.