Artificial Intelligence (AI) often conjures an image of a near-human like robot with intelligence rivaling or surpassing humans, with the intent of harming or dominating humanity. While AI may in some distant future reach a level surpassing humans, in its current form it is benign and drastically different than how we imagine it to be. The last few years has seen not only rise in the use of AI behind many platforms but also rise in investment in AI startups. In the last five years, have exceeded $20 billion and the market is expected to reach a value of $78 billion by 2025.

There are hundreds of companies in the AI market all vying to establish their expertise in specific markets and domains. The top markets that have emerged in recent years have been healthcare, cross-industry applications, cybersecurity, commerce, marketing, and finance. Yet the technologies used in each segment are not homogenous, AI is a broad umbrella encompassing multiple core technologies that act as the‘smart’ technology we perceive it as.

Top AI technology can be broadly segmented into the following categories:

  1. Machine Learning (ML)– advanced and even predictive data analysis using algorithms and statistical methods to teach specific systems to process and perform operations better. ML can better analyze large amounts of data and help organizations make better decisions based on the analysis.
  2. Natural Language Processing (NLP)/Speech Recognition – NLP enables software systems understand human language, measure sentiment, and analyze the text within a specific context. Speech recognize is understanding human speech and applying reason and logic to the speech that is analyzed. Amazon Alexa is a good example of speech recognition, it will recognize what is being asked of it and will subsequently respond appropriately.
  3. Image Processing – whether an AI system is analyzing a drivers face behind the wheels to determine if they are tired or analyzing an x-ray to determine results, image processing has vast potential to be used in multiple domains. In fact, an easy example is the implementation of facial recognition technology in more and more cars to alert drivers if they are tired.
  4. AI Assistant/Chatbots – Alexa, Siri, and Google Assistant are great examples of AI assistants in the market that respond to user questions with correct information.  Their speech recognition capabilities enables to understand what you asked it, quickly search the web and respond back with an appropriate answer. Chatbots, on the other hand, are smart systems part of a smart phone app or a website with which you can chat with. Chatbot will analyze what you are texting and respond back if there is someone on the other side of the screen is chatting with you. Chatbots help improve efficiency and workload in enterprise environment. For example, chatbots are used by insurance companies to assist people in lieu of customer service professionals to reduce workload. Chatbots are also used in healthcare to chat with patients to determine their symptoms (based on patient response) and determine what conditions they may be suffering to assist clinicians for better and quicker decision making.

Where is it used?

Many of us have probably seen advertisements for IBM Watson from few years ago where AI had near mythic status and few of us in the consumer market understood exactly what the AI did and how it was used. Much has changed from those days, AI is everywhere as we briefly discussed from some examples above. Some domains that are low-hanging fruits that can impact many of us are:

  1. Healthcare
  2. Business Intelligence
  3. Customer Relationship Management

Healthcare

Healthcare organizations can use machine learning to assess patient data from the Electronic Medical Records (EMR) and predict potential trends and outcomes for individual patients and or patient groups. Healthcare organizations can also use Chatbotsas part of their workflows to chat with patients before they come in for a visit to help clinicians make better determinations of patient symptoms and conditions. Alternatively, they can be used to follow up with patients after their visit to determine their health.Chatbots can serve as a powerful tool to augment clinician’s capabilities to automatically obtain deeper feedback from patients and stay informed of changes in patients symptoms. In fact, the unique nature of chatbots enables patients to freely respond to chatbotquestions that in turn prompts the chatbot to ask further questions about symptoms and subsequently present the findings to the clinical team. While it may not be 100% accurate, it is a powerful tool to reduce clinician workload.

Business Intelligence

Businesses of all sizes can utilize machine learning to analyze their business data to form better picture of their workflows and predict emergent patterns based on current financial and operational data. If your organization has ever-increasing and large volume of data, then machine learning can aid in optimizing how that data is processed, analyzed, and presented for better decision making. Another aspect of machine learning that is highly relevant to businesses is sentiment analysis. Businesses, especially marketing teams, can assess customer feedback of products and services by analyzing what customers say on social media or some other medium. Within business intelligence, decision are often driven by hard numbers; but with sentiment qualitative data can be organized similar to quantitative data for a more robust picture.

Customer Relationship Management (CRM)

For businesses, having the power to convert prospects into profitable customers is vital. While CRM platforms have empowered businesses of all sizes, the large amount if data can be difficult for sales team to sift through and organize. AI technologies can provide means for analyzing large datasets, provide recommendations to follow-up with particular leads, and determine the likelihood of closing deals in pipeline.

At PlenarTech, we focus on improving the ROI and efficiency of our healthcare and business clients by leveraging machine learning and natural language processing. The unique nature of AI technologies allows for flexibility in designing a solution that is uniquely tailored for your needs. With focus on human-centered design driven approach, we develop solutions by working with all stakeholders involved in the project. Feel free to reach out to us to learn more about how we can help your organization improve their performance.