Digital transformation has changed the daily lives of businesses and consumers. It has impacted the behaviours, needs and expectations of an increasingly demanding digital customer. Let’s dedicate this instalment to exposing how artificial intelligence (AI) and machine learning (Machine Learning or ML) have transformed the information technology (IT) customer experience.
AI and ML implementations reinvent and improve digital transformation processes, taking the IT customer experience to new levels. Photo by CreativeArt – Freepik.es
In a survey conducted by Salesforce, 88% of corporate customers say that the experience is as important as the quality of products and/or services.
The use of disruptive technologies such as Artificial Intelligence (AI) and machine learning (ML), within the internal processes of companies and information technology (IT) services, significantly impact the customer experience, while adding efficiency to processes and solutions.
In this article, we will look at the main trends where AI and ML technologies are transforming the customer experience in IT.
The impact of AI seen from another perspective: Web 3.0, NFT and AI: Impact on Technology Innovation Strategies.
AI and Machine Learning (ML) in the Context of IT Services
In the digital age, IT services have become the gateway to customers, whether through websites, social networks, or telephony. They may even become the only means of customer contact with companies.
This generates multiple areas of opportunity for companies, being able to collect preferences, behaviours and needs of customers through Big Data. Information that, when processed with the support of AI and ML, allows the generation of innovative and reliable solutions. All are adapted to the needs and preferences of customers.
When we talk about the implementation of AI, we must mention the subgroup of technologies involved:
- Machine Learning (ML)
- Deep Learning (DL)
- And Natural Language Processing (NPL)
Let’s talk a little about each of them.
Machine Learning (ML)
It is a sub-part of artificial intelligence focused on developing systems based on algorithms capable of learning from the data provided to them.
ML-based applications can generate patterns and even modify them if necessary. ML technology can analyze information, learn from it, and make decisions based on what it learns.
This branch of AI is essential for processing data associated with social networks and user interactions through digital media.
Functionalities that allow to detection of behavioural patterns, to identify improvements or new opportunities.
Deep Learning (DL)
It is a method of machine learning (ML) where the learning process is layered within neural networks, such as the IBM-Neural Model.
With the ability to process videos, sounds and non-analogous texts in large quantities. It can learn from the same processing it has done before.
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Natural Language Processing (NPL)
Natural Language Processing (NPL) is another branch of artificial intelligence that allows AI algorithms to understand human language and generate a coherent response through text or speech.
Its combination with the field of linguistics is what makes language interpretation and simulation possible.
Its application is used in a variety of applications, such as search, predictive text, and voice assistance. It is a fundamental basis for customer services with Chatbots, as reported by Gartner.
AI and ML Applications in Information Technology
According to the aforementioned Salesforce survey, 60% of business customers prefer to use digital media to contact companies.
It is even projected to continue growing in the coming years. This growth in the use of digital channels creates the need for IT services to be automated. And thus, they can provide users with the experience according to each profile.
The application of AI and ML technologies in IT gives companies extraordinary value by accelerating internal processes and optimizing the customer experience.
These are two factors that give companies responsiveness, and productivity, among other benefits, which directly affect profitability.
Let’s analyze three areas that are positively impacted, thanks to the application of AI and ML in IT services.
Quality Assurance
An important part of any IT implementation is the testing and certification processes of technologies, which are tied to human intervention.
This means that the reliability of software or hardware is not 100% in most cases. At the same time, it includes testing and improvement cycles, which delay the availability of the new technology.
By integrating AI and ML tools in IT development departments, it is possible:
- Test automation, complex tests are guaranteed regardless of the level of modifications.
- In the detection of errors or possible future failures, AI constantly monitors the information generated by the systems, predicting and detecting failures in time.
- Obtaining information on user behaviour, allowing the detection of new customer needs, while personalizing the service offered to each customer.
Additionally, automating processes and delegating repetitive responsibilities to AI and ML tools allows teams to focus on more strategic and innovative tasks.
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Customer Experience Optimization
Excellence in service delivery is something that all companies strive for. The incorporation of AI and ML brings companies closer to achieving this goal.
AI can use previously collected data, including behavioural information, interaction history, and the performance of the company’s services, and provide immediate responses to customers with possible solutions or recommendations, without the need for human intervention. In this way, the service centre would be automated, very much in the style of Service Desk implementations.
This has changed the way services are offered, transforming the customer experience, through the delivery of value, not only in the products or services offered, but also in the levels of attention offered.
Boosting process automation
The advantage offered by the integration of AI and ML in IT services focuses on process automation.
A trend that gives companies efficiency, accuracy, and scalability. Additionally, it gives them the knowledge they need to personalize their services and deliver value to customers at all touch points.
AI in IT Operations or AIOps
Artificial intelligence for information technology operations (AIOps) is a concept that involves the use of technologies such as Big Data, machine learning, natural language processing (NLP) and artificial intelligence (AI) in IT operations.
According to Gartner:
“AIOps platforms combine Big Data and ML functionality to enhance and partially replace all core IT operations functions, including availability and performance monitoring, event correlation and analysis, and IT service management and automation.”
This degree of automation simplifies IT operations while accelerating team responsiveness. Involving processes of observation (monitoring), resource optimization and problem determination.
According to IBM, AIOps is an evolution of the development and operations (DevOps) disciplines. Therefore, migration to AIOps platforms may generate less impact on companies that apply this collaborative methodology.
Going deeper into DevOps: Six reasons why DevOps is good for your business.
AI and ML in IT services: some use cases
The application of these technologies in IT services can be visualized on a daily basis, through social networks and tools we use every day. We could mention some of them:
- Image recognition, on Facebook automatically identifies friends and creates tags on photos. Reducing the time that the user must invest in this task.
- Product and content recommendation, platforms such as Amazon or Netflix, use the data collected from users, as well as their location and behaviours, to make recommendations.
- Fraud detection, AI is able to detect suspicious transactions autonomously and take action. Reducing cases of fraud, which directly impacts customer confidence.
- Assistance, virtual assistants such as Alexa or Siri, offer services supported by NLP and AI.
- Personalized searches, by implementing NLP, search engines can perform searches interpreting what the user requires according to the context. The search results are then returned according to the intention of the searcher.
There are also applications in the field of driving, health, sales, and marketing, among others. Most of them are focused on offering more and better services to their customers.
AI & ML in the IT customer experience – Conclusion
IT will continue to evolve, and companies risk falling out of the competition if they turn their backs on this reality.
As PWC points out, “AI success is becoming the rule, not the exception.”
Being in the era of data, companies must be able to collect, analyze, process and act immediately to the needs and requirements of both the industry in which they operate, as well as customers. All are supported by an ever-deeper implementation of AI and ML.
AI and ML technologies in IT services support the growth of companies, transforming the way services are provided with automation that optimizes the customer experience.
Through service personalization, immediate responses generate value and products that adapt to their needs.
For Nulogic supporting companies in these digital transformation processes is a priority, we are pioneers in America and Latin American countries for Cloud implementations, transformation, and digital maturity for different sectors.