The Impact of AI on the BA Role

 

When I started teaching VoiceXML at Seneca College in Toronto, Canada years ago, I didn't realize I was embarking on a 4 year teaching career in AI. VoiceXML is a natural language speech recognition software, which involves automated voice communications. It's a feature-rich computer language for building interactive voice response (IVR) applications. Natural Language Processing (NLP) is a sub-field of AI where natural language data is processed and analyzed by computers. You may be familiar with ringing up any call centre, and receiving a voice chatbot asking you "Tell me what you want to do today." Algorithms detect your voice, and provide customer-friendly responses based on interpretation of your words. IVR systems discern intent, and can be used for a variety of services from banking transactions, to mobile purchases, online retail orders, and travel bookings. It begs the question, how can the business analyst have a space in the world of AI?

"Nothing is so painful to the human mind as a great and sudden change." (Mary Shelly, Frankenstein). AI is certainly a great and sudden change in the IT world, but perhaps not as frightening as Frankenstein. Change is at the core of what business analysts do, and change in the AI field is more prevalent today than ever. So, what type of impact does this change have on the role of the business analyst in AI?

Interactive Voice Response (IVR)
AI adoption is on the increase in businesses, and IVR is an area where there is large demand for business analysts. As businesses increase economies of scale and expand collaboration, there will be a stronger focus on AI tools, practices and procedures, at the centre of which will be people and data. This is where BAs will thrive on a grand scale within AI.

For example, an IVR Business Analyst might work directly with call centre leadership, telephony support teams, or network with vendors to determine business solutions for the IVR applications. AI could report on IVR retention and success levels, and fine tune speech recognition analysis in applications like Nuance Application Report (NAR) or IBM Watson. The BA would be responsible to manage the requirements needed to be programmed into the IVR system. And, the BA would be able to interpret and articulate that output data for management and C-Suite executives, to enable them to make informed strategic business decisions.

An IVR BA could also make recommendations on speech and touch-tone user interface design enhancements, and focus on managing risk within IVR systems by liaising with legal, audit, and risk and compliance teams. This involves effective communication skills, a key ingredient for all BAs. As a conduit between business customers and the technical teams, an IVR BA would still have to identify issues or gaps where crucial technical and business solutions need to be made.  

Radio-Frequency Identification (RFID)
RFID is a form of automatic identification and data capture (AIDC). RFID technology uses electromagnetic signatures with radio frequencies to capture data. For example, using tags RFID can track inventory goods like automobiles during assembly line production, or for pharmaceuticals in warehouses. And, it can be implanted in animals as a microchip to track livestock or pets. RFID tags can also be attached to money, clothing, various possessions, and even people. All the data collected from these tags need to be interpreted by BAs, to determine and understand product trends within the market place. RFID has been projected to grow to $15 billion USD within 2021.  This is definitely an expanding area where BAs in the AI field are in much demand.

Brand Marketing
Noticing and understanding marketing trends are paramount for many businesses, and is a task within the AI sphere where BAs are much needed. For instance, social media campaigns are heavily influenced by the data gathered from TagBoard, which collects hashtag information from social media, or from OneQube, which is an audience development platform. Business Analysts would manage these tools, which track online conversations that focus on detecting keyword usage associated with branding. Of course, this inevitably influences target advertising and marketing use cases via AI.

Crunching and calculating all this data would be done by AI software, while the BA would be better suited to interpreting the analytical data. The results from data queries and reports can be used to understand customer patterns of behaviour, which enables businesses to personalize products based on geographic location, income, age, gender, and a myriad of other categories. Segmenting customer characteristics is at the core of AI. Undoubtedly the outcomes from predictive analytics can heavily impact customer purchasing decisions, allowing more streamlined access to new markets or to new products, delivering products faster to market with greater value, being first to market, or forging new business ventures.

Whether in banking, manufacturing, retail, tourism, and the like, a BA can use data points, produced through AI, to discover what motivates a customer to access a business, and what converts that movement into sales. The objective is influencing buyer behaviour, improving quality assurance, and increasing competitive advantage. 

GPS
I once rented a minivan for a return road trip from Phoenix, Arizona to Southern Utah. It turns out these minivans are equipped with GPS technology. Imagine the hundreds of rental minivans and rental cars all over the world that are being tracked by GPS technology. All this data is collected, managed and analyzed by AI software. BAs are needed to interpret this data to maintain quality customer service: to predict when vehicle maintenance is required; to locate customers during an emergency; to learn how to market a wider range of customers, and so on.

Conclusion
Whether it be IVR, RFID, brand marketing, or GPS, BAs can work within different contexts using a variety of tools from root cause analysis to decision modelling, to determine the performance levels of organizations. 

The BA can look at the holistic picture, and with the assistance of AI, can break down large projects into smaller manageable bite-sized chunks, devote more focus on the crucial people aspect of the business, and contribute to interpreting deeper insights into rich data. These aspects are instrumental in exploiting services and increasing ROI for businesses.

By leveraging AI, a BA’s role within an organization can ultimately be enhanced by effectively adapting to change, no matter how great, and devoting more time to contribute to critical business decisions. Such decisions could include forecasting market trends, providing different perspectives on a problem, facilitating workshops, collaborating with key stakeholders, enhancing current capabilities, understanding customer environments, or promoting an AI strategy, all of which add immense value to a business.