Feature
The Gist
- Driving innovation. AI optimizes operations and enhances customer experiences via advanced algorithms, data analytics and machine learning.
- Boosting efficiency. AI technologies like chatbots and intelligent process automation streamline business processes, freeing up resources for complex tasks.
- Fostering growth. With a staggering $142.3 billion global market, AI is at the core of transformative technologies and a key player in industries' digital transformation.
Artificial intelligence (AI) is revolutionizing the process of digital transformation, providing opportunities for businesses to optimize their operations and enhance customer experiences. By embracing AI technologies, brands can take advantage of advanced algorithms, data analytics, and machine learning to drive innovation and stay ahead of competitors.
Through the use of AI, brands are able to automate repetitive tasks, extract actionable insights from extremely large volumes of data and create personalized customer experiences. From chatbots to predictive analytics and process automation, AI is reshaping the way businesses approach digital transformation, bringing efficiency, agility and customer-centric functionality to the forefront.
As of June 2023, the global AI market has skyrocketed to a staggering $142.3 billion, according to a recent Statista report. The surge is primarily fueled by AI’s transformative applications in customer experience enhancement, insightful data analytics for customer trends and the increasingly popular field of generative AI. Additionally, a May 2023 Statista report revealed that AI, big data and the cloud are the core transformative technologies with broad applications across industries. This article will examine the many ways that AI is impacting digital transformation.
AI & Data Analytics
One key aspect of AI's impact on digital transformation lies in its ability to analyze and interpret large volumes of data in real-time. With AI-driven analytics, brands can gain deep insights into customer behaviors, preferences and trends, enabling them to make data-driven decisions and create highly tailored experiences.
Data analytics can help in segmenting customers based on various criteria such as demographics, buying behavior and preferences. This segmentation enables businesses to tailor communication and marketing strategies for different customer groups, resulting in a more personalized experience.
The use of AI for data analytics is a great example of how AI is transforming businesses across industries. Jeff Fraleigh, president of ETI Software Solutions, a broadband platform and services provider, told CMSWire that AI can be used to analyze data from sensors and other sources to predict when critical telecommunications equipment is likely to fail. “This allows operators to schedule maintenance before problems occur, which can prevent outages and improve network reliability. This enables them to fix issues before consumers even realize it.”
Additionally, Fraleigh said that AI can be used to analyze data on network usage and traffic patterns to help network operators and Internet Service Providers plan and optimize their networks. “This can help operators to improve network performance and capacity, and it can also help them to reduce costs. For example, AI can be used to identify areas of high traffic congestion and to recommend solutions to alleviate the congestion.”
AI & Customer Support Chatbots
AI is also transforming customer interactions and support through the use of intelligent chatbots and virtual assistants. These AI-driven generative and conversational chat agents are able to provide instant and accurate responses to customer inquiries 24 hours a day. Businesses in various industries, such as online retail, banking and telecommunications, are using AI chatbots to handle routine customer queries, freeing up human agents to focus on more complex tasks. This enhances customer service, reduces response times and improves the overall customer experience.
Although chatbots have been ubiquitous for many years, today’s chatbots are powered by generative and conversational AI that provides customers with multiple ways to find solutions, solve problems or direct them to the most appropriate live agent. Being able to help themselves through the use of chatbots also enables them to control their own narrative, leaving the customer feeling satisfied and emotionally in control. These AI-driven chatbots also free live agents to handle more complex service issues, saving them from the redundancy of answering routine and mundane queries.
One example of how AI-driven chatbots are transforming the digital landscape is that of Boost.ai, whose client Michigan State University Federal Credit Union (MSUFCU) test drives different technical pilots through The Lab at MSUFCU to better serve their members' financial needs and provide a better overall experience. One of its test programs introduced its first virtual agent, Fran, which eventually led to a full implementation. This allowed them to provide 24/7 support for their members, answering common questions, and providing more relevant responses and services. Over the first two weeks, Fran resolved 81.1% of queries. Less than two years after the implementation, Fran’s query resolution rate was 98%, experienced a 620% increase in MSUFCU's intent library and had over 200,000 member conversations.
Related Article: 10 Top Chatbot Providers You Should Know About in 2023
Intelligent Process Automation
In addition to customer-facing applications, AI is driving process automation and optimization across various business functions. By automating repetitive and manual tasks, AI-powered systems can significantly improve operational efficiency and productivity. For example, in the healthcare industry, AI algorithms are used to analyze medical records, diagnose diseases and recommend personalized treatment plans, enabling healthcare professionals to deliver more accurate and efficient care.
Traditionally, AI is driven by data, whereas robotic process automation (RPA) is driven by rules. By integrating AI into RPA, brands can automate a broader range of processes and are not limited to the simple, rule-based tasks. This integration also makes automation more resilient and adaptable to changes, which is particularly important in dynamic business environments. The integration of AI with RPA is often referred to as intelligent process automation (IPA) or smart RPA. This combination allows RPA to handle more complex tasks that involve unstructured data, natural language processing, decision-making and learning from experience.
For Fraleigh’s broadband business, AI is used to automate the process of network planning. “This can free up human resources to focus on other tasks, and it can also help to improve the accuracy and efficiency of the planning process. For example, AI can be used to generate network plans based on a variety of factors, such as traffic patterns, budget constraints, and regulatory requirements,” Fraleigh explained.
Sharad Varshney, CEO of OvalEdge, a data catalog and end-to-end governance solutions provider, told CMSWire that there are other important benefits aside from the time and cost savings when you shift manual workloads to automated processes. "Using AI to classify data enables you to pull out and identify the PII, sensitive, and confidential data in your organization," said Varshney. "This knowledge supports transparent auditing and accelerates data adoption and access because access policies can be built more quickly based on these AI-driven classification results."
The Impact of AI on Predictive Analytics
AI-powered predictive analytics is another area where digital transformation is being revolutionized. By using historical data and machine learning algorithms, brands can make accurate forecasts and predictions, allowing them to proactively address challenges and take advantage of the opportunities that are presented. For instance, retail companies use AI algorithms to analyze customer purchase patterns and predict future demand, optimizing inventory management and ensuring the availability of popular products.
The high-velocity, fast-paced nature of today’s consumer interactions requires that brands possess the ability to respond to changing circumstances in real-time. By integrating real-time analytics into predictive models, brands can make split-second decisions that are essential in providing an exceptional customer experience.
Netflix, for example, uses both predictive and data analytics to provide personalized recommendations to its customers. They are able to do this with 80% accuracy by analyzing their customers’ watch history, search history, demographics, ratings and preferences. Similarly, other brands such as Spotify use AI algorithms to generate personalized playlists that cater to individual tastes. This level of personalization enhances the user experience and strengthens customer loyalty.
Ryan Fannon, director of product management at UPS Capital, a shipping insurance and alternative financial services provider, told CMSWire that the logistics industry is using predictive analytics to discover address-related data to determine the various levels of risk in certain delivery areas. “In an age of uncertain shipping experiences and the need for best-in-class customer experiences, modern predictive analytics are a necessity for businesses.” Fannon explained that the data provides merchants with insights about the risk level of certain delivery areas, which enables them to decide if additional safeguards should be put into place.
Additionally, while predictive analytics provides the ability to forecast potential scenarios, prescriptive analytics takes it a step further by suggesting the best course of action to capitalize on these predictions. Integrating prescriptive analytics into customer experience initiatives enables brands to not only anticipate customer needs but to dynamically adapt and optimize their strategies to exceed customer expectations.
Related Article: The 5 Stages of Predictive Analytics for CX Success
Customer Insights and Sentiment Analysis
In the realm of marketing, AI is transforming customer insights and targeting strategies. The vast amount of data that is generated from customer interactions is a veritable treasure trove of opportunities. By using AI and machine learning, brands can extract granular insights from this valuable data. AI, when used with sentiment analysis, has the ability to forecast not only customer behavior but also the emotions behind these behaviors. This allows brands to tailor customer journeys that are both emotionally enriching and contextually aligned.
AI-powered sentiment analysis is enabling brands to decipher customer emotions from all of their channels, including social media posts, chat discussions, product reviews, and customer service calls. Additionally, many brands are using sentiment analysis along with social listening to more fully understand the emotions and feelings behind the words of their customers’ social media posts.
Joel Martins, chief technology officer at Calabrio, the workforce performance company, told CMSWire the goal of sentiment analysis is to understand what a customer means, not just what they are saying. “It is amazing, companies no longer need to monitor individual calls to discern how a consumer feels about their business," said Martins. "Sentiment analysis provides an immediate score (positive, neutral, or negative) for every customer interaction. AI-powered sentiment analysis uses advanced text and speech-to-text analytics to identify keywords and phrases that signal the emotional tone and the underlying sentiment behind a customer’s words.”
Martins explained that instead of waiting for a customer to tell a business that they’re unhappy, sentiment analysis highlights negative or positive experiences in real-time.
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Final Thoughts AI and Digital Transformation
AI is fundamentally changing digital transformation. Through the use of AI-powered technologies, brands can create new opportunities for growth, efficiency and customer experience. From personalized experiences and intelligent automation to advanced analytics and predictive capabilities, AI is reshaping (and disrupting) industries across the board. By embracing AI's potential, businesses can improve the digital transformation process, stay competitive and provide their customers with exceptional products, services and experiences.
