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  • 7 reasons to incorporate AI into your customer service strategy

    7 reasons to incorporate AI into your customer service strategy

    The year 2023 will be remembered, among other milestones, for the launch of the GPT-4 model. The emergence of Artificial Intelligence (AI) has brought about a revolution in all sectors and in all areas of life.

    And the Customer Experience sector is no exception. AI has become an indispensable tool for process optimization and why not apply it to a Customer Service strategy to improve the customer experience.

    We have made a brief exercise to identify the main reasons why we believe that Customer Care can benefit significantly from its incorporation.

    One of the reasons to incorporate AI into your customer service strategy is to generate efficiencies by automating repetitive processes.
    One of the reasons to incorporate AI into your customer service strategy is to generate efficiencies by automating repetitive processes.

    AI in your customer service strategy

    Here we share the top 7 reasons why you should incorporate AI into your Customer Service strategy:

    1. Coverage of activity peaks

     

    One of the biggest problems we face in the sector and which worries the companies we work with, is the coverage of activity peaks in time slots, specific days, specific months… Dimensioning, reinforcement plans with floating resources, many times these peaks are difficult to cover without creating other types of inefficiencies (economic, quality, etc.). In all businesses, the activity is not sized for peaks, but for a normal activity with a slight oversizing of resources.

    The scalability of Conversational Assistants with AI guarantees the coverage of these peaks of contact that we can experience in our services. Regardless of the time or day, conversational assistants absorb these volumes (whether expected or not) without any additional effort.

     

    2.Reducing waiting times

     

    Closely related to the activity peaks we find waiting times, a headache for services that handle multiple channels and high volumes of contacts.

    Regardless of the query they want to make, customers hang up and call back, generating callbacks and service saturation. Many times, in a given time interval, there are 4 or 5 calls from the same customer who is forced to wait, hang up and redial… The scalability and flexibility provided by Conversational Assistants allows us to reduce this situation to its minimum expression, or even eliminate customer waiting times completely.

    But wait times are not the only thing we can reduce considerably. Response times can be drastically reduced thanks to the ability to provide instant answers to common queries.

     

    3. Personalization of the attention

     

    AI and automation are not aopposed to the personalization of customer service, quite the contrary. The possibility of being able to integrate conversational assistants with CRMs and other systems allows the personalization of messages, information and even opens the door to anticipate possible customer needs or requests.

    We can analyze customer data to provide personalized responses and recommendations. This creates a more individualized experience for each user, improving customer satisfaction and loyalty.

     

    4.  Extended hours of operation

     

    Fortunately, Artificial Intelligence has no time constraints and can provide 24/7 assistance. This improves accessibility for customers in different time zones and makes it possible to solve problems outside working hours.

    Our customers’ service demands are not always generated within the operating hours that have been determined; if we give our customers the possibility to solve their queries or problems at the time they arise, we will certainly have more satisfied customers.

     

    5.  Process automation

     

    AI can automate repetitive tasks and routine processes, allowing customer service agents to focus on more complex and strategic tasks. By automating tasks through AI, it is possible to reduce the workload of customer service personnel, thereby creating efficiencies and lowering the operational costs associated with processes that are not handled by agents.

     

    6. Cost reduction

     

    What is clear is that incorporating Artificial Intelligence into the Customer Service strategy can bring important benefits such as those listed above. However, it is also necessary to consider the possibility of reducing costs thanks to its implementation. In this particular case, reducing costs is not synonymous with reducing levels of attention or service, but quite the opposite. The use of AI will help us to enhance a more satisfactory experience at a lower cost.

     

    7. Align yourself with industry trends and the future of customer services.

     

    Customer satisfaction is and will continue to be the main objective in customer services, and Artificial Intelligence is undoubtedly being a determining element in creating efficiencies and improving customer satisfaction. It is time to incorporate innovative solutions and take advantage of AI capabilities in order to modernize a sector that is still very traditional. The goal is to become more efficient and competitive in creating customer services that provide customers with a “Best in Class” experience.

     

    The ability to solve problems in an efficient and personalized approach contributes to customer satisfaction and strengthens brand perception.
    The ability to solve problems in an efficient and personalized approach contributes to customer satisfaction and strengthens brand perception.

     

    These are just 7 reasons why you should incorporate AI in your customer service strategy, although we are convinced that there are many more…

    Would you like to know how AI can help you to exponentially improve your customers’ experience?

    Book your demo here and we will tell you how MAIA Cognitive can make a difference in your Customer Service strategy.

     

  • Coexistence of conversational assistants and agents

    Coexistence of conversational assistants and agents

    AI is here to stay

    In recent times much has been said about the possibility that AI will replace jobs and that we are easily replaceable. The world of customer service and the contact center has been no exception, but… How much truth is there in this? Do we opt for Conversational Assistants or Agents?

    Can AI really replace an agent? To reach a conclusion it is necessary to address some basic concepts.

     

    Conversational Assistants or Agents? AI has arrived to become the great ally of agents and help them focus on much more complex and less repetitive tasks.
    Conversational Assistants or Agents? AI has arrived to become the great ally of agents and help them focus on much more complex and less repetitive tasks.

    What is an AI-based Conversational Assistant?

    An AI-based Conversational Assistant is primarily designed to interact with users through natural language conversations. They can answer questions, perform specific tasks and provide information by both text and voice. They can perform multiple tasks, from providing basic information to performing more complex actions, such as making reservations, providing recommendations or even performing transactions.

    What is an Agent?

    Agents are people who act on behalf of an organization in order to help other people in management and functions with different degrees of complexity. They are able to empathize, negotiate and understand more complex and unexpected human situations.

    Conversational Assistants or Agents?

    It’s a good question, do we opt for Conversational Assistants or Agents, which of the two strategies would be more successful?

    To include only human agents or to include only AI in the contact center?

    Only use agents

    For years we have used only agents in Contact Centers and it has seemed to us the most logical and correct thing to do, but with the introduction of new technologies we have noticed that there are certain improvements that we cannot overlook.

    For example, using only agents entails high operating costs, it is not very scalable if there are large volumes of calls, the response time may be higher, among others.

    Use only AI

    n this case we are faced with a real impossibility of using intrinsic human skills such as, for example, negotiation skills, management of unexpected situations, lack of empathy and context.

    With Conversational Assistants we achieve greater scalability by allowing, among other things:

    • Automation of repetitive tasks
    • Fast and consistent responses
    • 24/7 support
    • Efficiency and scalability by handling large volumes of queries simultaneously

    In addition, Conversational Assistants are able to personalize the answers they give to customers thanks to integrations with other systems such as CRMs.

    The ideal scenario

    Both options have pros and cons. However, the ideal scenario is the integration and synergy of both resources.

    Agents should handle complex and less repetitive situations, without losing focus and customer orientation. While AI can handle repetitive tasks and provide information quickly and efficiently.

    The key is to find a balance that leverages the best of both worlds to deliver a comprehensive and satisfying customer experience. This combination of the two will exponentially improve productivity rates and customer experience.

    In conclusion, increased productivity, cost savings and improved customer experience is only possible with the effective combination of physical agents and AI, as it is the ideal formula to maximize the strengths of each and deliver the best of both worlds to the customer.

    Are you ready to take the leap? Here’s how MAIA Cognitive can help you

     

  • Artificial intelligence in insurance

    Artificial intelligence in insurance

    Introduction

    Artificial Intelligence is having a significant impact today and the insurance industry is no exception. In the insurance industry AI is being used to improve customer experience, operational efficiency and profitability.

    Conversational AI is a technology that enables communication between computers and people through natural language, both written and spoken. Conversational AI is based on natural language processing (NLP), which is the ability to analyze, understand and generate human language.

    If you want to know more about Conversational AI read our article: “What is Conversational AI and how did we get here?”

     

    Technological advances promise a significant expansion of Conversational Artificial Intelligences in the insurance sector.
    Technological advances promise a significant expansion of Conversational Artificial Intelligences in the insurance sector.

    Fields of application of AI in the Insurance Sector

    It helps insurers to manage claims more efficiently and effectively. For example, conversational AI is used to facilitate communication and coordination between the different actors involved in the process, such as the client, the adjuster, the garage or the insurer, and to optimize resource allocation and decision making. All this allows faster and more informed decisions to be made.

    Risk assessment

    In this sense, Artificial Intelligence refines risk assessment, enabling the collection and accurate analysis of data from various sources, such as electronic sensors, social networks, medical records or public records. In addition, it enables the creation of predictive models capable of estimating more accurately the probability and impact of potential adverse events, thus allowing early warnings to policyholders.

    Personalization of products and services

    AI can help us to accurately identify the varied needs, preferences and expectations of individual customers. This approach translates into the creation of personalized proposals that are specifically tailored to each risk profile. Moreover, these proposals can be communicated by conversational AI through various channels such as WhatsApp, emails, voice or other channels agreed between the company and the customer.

    Fraud prevention

    Fraud prevention is crucial for insurance companies, as it helps minimize financial losses, establish competitive rates and preserve customer confidence by ensuring integrity and fairness in claims handling.

    Using anomaly detection techniques, the establishment of verification and validation mechanisms are actions that can currently be carried out by Artificial Intelligence developments. Conversational AI facilitates the identification of verification patterns or identify specific terms that may indicate fraud or inconsistencies in the customer’s history, potential signs of deception.

     

    The Future of Conversational AI in the Insurance Industry

    Technological advances promise a significant expansion of Conversational Artificial Intelligences in the insurance sector. Further automation is foreseen, not only in existing processes, but also in the creation of new innovative products. The emergence of these products will allow the creation of insurance products that are more adapted to the singularities of the users, thus marking a significant change in the services offered in the sector.

    Exploration of case studies on Artificial Intelligence in general in the insurance sector.

    After a brief investigation of the sector, we have been able to identify companies that have applied AI in business processes with interesting results. Some examples of these case studies are:

    • The analysis of customer claims and assignment to the most appropriate claims managers according to their complexity and urgency. The system also helps to detect potential fraud and improve customer satisfaction.
    • Offering travel insurance based on real-time flight data. The systems are able to use blockchain-based smart contracts to automate the payment of compensation in case of flight delays or cancellations, without the need for the customer to file a claim.
    • Machine learning to analyze claims data, underwriting and other processes. A company that applied artificial intelligence to these processes and among the benefits were: reduced fraudulent claims, increased underwriting accuracy and optimized business processes.
    • Using machine learning to analyze weather trend data, traffic data and other data, which has helped the company better understand the risks associated with extreme weather events, driver behavior and other factors.

    In summary, companies in the insurance sector are progressively integrating artificial intelligence into the core of their business structure. In this context, conversational artificial intelligence plays a crucial role in the smooth interaction in a sector where there are certainly many players, such as the customer, the adjuster, the workshop, the mediator or the insurer…

    Want to see how MAIA can help improve your business processes and customer experience? Book your demo here.

     

  • 5 AI predictions for 2024

    The year 2023 will be remembered as the year of Artificial Intelligence, without a doubt. However, we don’t want to end it without launching our 5 AI predictions for 2024.

    There are many headlines in which the AI has had all the limelight, but undoubtedly, what has meant a before and after, has been the launch of the GPT-4 model on March 14, 2023.

    Now the question that arises is what does AI have in hold for us in 2024?

    Our team has joined forces to explore the fascinating possibilities that artificial intelligence holds for us, and have released their predictions for the coming year.

    5 AI predictions for 2024

    5 AI predictions

    Rubén, our AI Specialist, tells us that by 2024 the use of ChatGPT-type LLM technologies in large companies will be massive. Although the margin for improvement of these technologies will not be too high, there will be an increase in several industries for the adoption of these technologies.

    Discover below our 5 AI predictions for 2024:

    1. LLMs integrated into mobile devices and glasses.

    Our Head of Digital Services & Innovation tells us that we will start to see AI in a variety of devices.AI will start to be seen in a variety of devices..

    “Artificial Intelligence is going to continue to evolve and make our lives easier and simpler

    During 2024 we will see how LLM (large language models) engines will be integrated into video devices (mobile phones, glasses…) and we will be able to start asking conversational assistants what we have in front of us and how they can help us to do certain types of tasks.”

    Can you imagine walking down the street wearing your sunglasses and chatting with an assistant giving you directions to your destination? This is undoubtedly a reality that is getting closer every day.

    2. Code generation, integration and deployment

    Javier, the team’s Data Engineer.

    “By 2024, code generation will be fully exploited, as well as continuous integration and deployment through generative AI, which will greatly facilitate the daily work of data engineers.”

    3. Consolidation of AI, especially in education, healthcare and marketing.

    Chema, Junior NLP Specialist of the team..

    “My prediction is that generative AI in particular will become well established in the market, especially in education, healthcare and marketing.

    Where it will have the greatest impact, in my opinion, will be in education, since students are developing a large amount of educational work with the help of ChatGPT; teachers will have to adapt to this trend, which is not an easy task.

    On the other hand, in the healthcare field, its use will be standardized for the recognition of diagnostic images and the monitoring of hospitalized patients; without forgetting how customer service will be positively affected, to a great extent, by the use of AI for the management of appointments, communication of results, among other tasks.

    Finally, in terms of marketing and advertising, we are already seeing the first “influencers” made with AI appearing, and it is very likely that this type of advertising will become consolidated and normalized in the industry.”

    4. Application in different areas within the daily life of the companies.

    Lorena, Business Innovation Consultant

    “Diversification of AI and its application in various areas within the daily life of companies.

    In an uncertain economic context, companies will begin to focus on automating and incorporating increasingly precise and accurate processes with the use of AI in all possible areas. All this will have an impact on the training needs of workers, so we will see a significant increase in training, specializations and AI courses for employees.”

    5. Regulations and agreements for the responsible use of AI

    Karina, IT & Digital Presales Senior Consultant.

    “My prediction for 2024 is that it will be the year of regulations and agreements for the responsible use of AI. We have already witnessed how the European Union (EU) institutions have reached an agreement on the key aspects and components of the so-called responsible use of AI Artificial Intelligence (AI) Act. This is the world’s first comprehensive law in this area, which, in my view, should be considered very good news.

    I personally believe that AI has many good things to provide us with and one way to be able to continue researching and developing its capabilities in a responsible way is to legislate and standardize its use at an international level ensuring that it is safe, transparent, traceable and non-discriminatory.”

     

    Innovation is just a click away. Find out how MAIA can be your partner for an unprecedented 2024.

  • How AI is radically changing customer service at Telcos

    How AI is radically changing customer service at Telcos

     

    Customer service is in a constant process of evolution. The emergence of conversational Artificial Intelligence (AI) is being a true revolution in the transformation of this industry. In particular, in the telecommunications sector, where speed and efficiency are crucial, AI-based solutions have proven to be indispensable tools for improving the customer experience. In the context of customer service in the Telecommunications sector, MAIA Cognitive, has stood out as a pioneering technology.

    The implementation of conversational AI has radically changed the way telecommunications companies interact with their customers. Previously, queries and problems often required long waiting periods and complicated resolution processes. Now, thanks to natural language processing, customers can get instant answers and accurate solutions through natural conversations with MAIA.

     

    In customer service in the telecommunications sector, the tandem of virtual agent and human agent reduces waiting times for customers and increases the ability to handle peak demand.
    In customer service in the telecommunications sector, the tandem of virtual agent and human agent reduces waiting times for customers and increases the ability to handle peak demand.

    Let’s talk about the advantages?

    But what are some of the advantages it provides in customer service in the telecommunications sector? In addition to total availability, i.e., being able to have assistance at any time and any day of the week, it can provide accurate and personalized responses.

    Resource optimization and operational efficiency is another feature to highlight within Conversational AI. Technology such as MAIA Cognitive can cope with a large volume of queries simultaneously, freeing agents to handle complex problems that customers may have. This tandem of virtual agent and human agent reduces waiting times for customers and increases the ability to handle peak demand without compromising service quality.

    Likewise, one of the fundamental characteristics of MAIA Cognitive is data governance, that is, storing all data correctly in order to be able to exploit it. Storing data correctly allows us to analyze what has happened, identify patterns of behavior and make predictions for the future, anticipating customer needs and potential problems.

    In addition, it can provide proactive solutions before customers raise concerns, which not only streamlines the resolution process, but also demonstrates a proactive commitment to customer satisfaction. So MAIA Cognitive’s technology not only answers questions, but can also anticipate customer needs, providing a more proactive and satisfying experience. Optimizing, of course, customer service in general.

    If you want to know more advantages, we recommend our article: “Artificial Intelligence arrives to revolutionize customer service efficiency”

    Let’s talk about the future

    The future of telecommunications sector is looking exciting as we continue to see consolidation among the major operators, as well as the incorporation of new technologies and service offerings. Therefore, the incorporation of AI will be key to success in the Telco industry and other sectors.

    As we move towards an increasingly digitized future, the potential for AI in customer care is limitless. From improving operational efficiency to delivering more personalized customer experiences.

    Conversational AI, particularly with products like MAIA Cognitive, is taking customer care to a new dimension. Shall we talk?

     

  • AI and the transformation of the CX in Banking (I)

    Finance is a fundamental part of our daily lives, and of course, banking services are essential in modern society. In recent years, technology has transformed the banking industry and the way we relate to it. Artificial Intelligence (AI) and the transformation of the Customer Experience (CX) in Banking are closely related.

    Evolution of the Banking Sector

    There are many changes that we have witnessed in the banking sector in recent years, among others, we can list by way of example:

    • Digital Banking, nowadays all banks have digital platforms that allow us, in self-service mode, to carry out all kinds of operations and transacctions: account opening, transfers, currency exchange, investment in stock markets…
    • Conversational Banking which, using “digital banking” platforms, has enabled banking and customers to interact in real time through text messaging, voice, mobile applications, messaging apps and websites to offer new channels of contact and unprecedented levels of service; let’s not forget that the goal of the “digital banking” is to “empower customers and banks to interact in real time through text messaging, voice, mobile applications, messaging apps and websites to offer new channels of contact and unprecedented levels of service. Let’s not forget that the objective of “Conversational Banking” is to try to reproduce the experience of the “offline” customer relationship and provide a complete and quality online experience.
    • The Open Banking which, following regulation by the European Parliament in 2015 (Payment Services Directive PSD2, Directive (EU) 2015/2366), has brought about a decisive change by promoting the development and use of innovative solutions that are integrated into the ecosystem of banking solutions thanks to the use of APIs.
    • The emergence of Neobanks and Fintechs, whose core business is fully aligned with digital and innovation, have opened the doors to a multitude of competitive and innovative services in the sector.

     

    Artificial Intelligence has had a special impact on the Transformation of the Customer Experience in Banking. Virtual assistants are here to stay and facilitate multiple operations for customers.

    Application of AI in Banking

    The use of AI in banks is not new; investment banks, for example, have used AI and Machine Learning long before other sectors to predict behavioral patterns. Over the last decade, banking has embraced AI in a variety of ways to improve operational efficiency, customer experience and decision making.

    Banks are currently applying AI to create portfolios, choose assets, perform analysis of large financial data sets, fraud detection, make predictions of economic trends and investment risks.

    The opportunities for AI applications go beyond basic banking activities. Implementing AI in customer interactions, in line with strategies such as “conversational banking,” among other things, makes it possible to manage frequently asked questions and provide quick answers to customers or personalized recommendations for banking or financial products and services, improving the customer experience and customer service and extending its coverage to 24/7.

    In a recent study, the McKinsey Global Institute (MGI) has estimated that, in the Banking sector, Generative AI also known as “GenAI” could have a huge impact generating an additional value of between $200 billion and $340 billion per year; all this by increasing productivity in functions such as marketing, sales and customer interactions, among other use cases. [1].

    Use cases of conversational AI in Banking

    If we put the focus on marketing activities and customer interaction, we can consider multiple use cases for Artificial Intelligence, but in this specific article we will focus on Conversational AI.

    Conversational AI is a branch of artificial intelligence that simulates human conversations (if you want to know more about Conversational AI, you can read our article: “What is Conversational AI and how did we get here“).

    The strategies of closure and reduction of physical offices of banks, due to the growing demand by customers for non-face-to-face services, have transferred a significant volume of these face-to-face interactions to the digital customer service channels that banks make available to their customers: digital banking, telephone banking…

    Perhaps the most relevant use cases for the application of Conversational AI in Banking are focused on the automation of conversations through AI Conversational Assistants or intelligent banking assistants.

    Banking Assistants

    AI has been integrated into mobile apps and voice assistants, allowing customers to perform banking transactions, check balances and obtain current financial information immediately through voice commands.

    Recommendations of personalized products and services, such as savings accounts, credit cards or investments.

    Wizards for improved Customer Service, thanks to the attention of frequently asked questions and provide quick answers to customers online, improving customer service 24 hours a day.

    Benefits of Conversational AIs in Banking

    We can not fail to review some of the key benefits from a Customer Experience (CX) perspective, we could surely list many more, but to point out the most important ones are:

    • Extending customer service and transactional request management to channels with high demand such as WhatsApp or chats in a fully automated way.
    • Improving accessibility to services for groups with disabilities or the elderly after the disappearance of physical offices, adapting the experience to their needs and most common operations and keeping open the possibility of referring them to other services.
    • Hyper-personalization of the customer experience based on data analysis, with the possibility of personalized notifications and recommendations.
    • Service improvement and offer prospecting taking into account real customer demands.

    Additionally, it is not easy to ignore the economic impact that AI could bring to the banking sector equivalent to an additional value of between 200 and 340 billion dollars per year! A not inconsiderable sum…

    Challenges of AI in Banking

    The integration of artificial intelligence (AI) in the banking sector, while promising, is not without significant challenges. Challenges that are not entirely different from those found in other sectors.

    Protecting the privacy of financial data becomes crucial, with the need to ensure robust security measures. In addition, AI, lacking a full understanding of the human context, faces challenges in interpreting nuances and making ethical decisions, underscoring the importance of addressing these issues for effective and ethical deployment in future banking.

    In conclusion, the integration of Artificial Intelligence taking place in the banking sector has marked a significant milestone, as it is redefining the customer experience. From intelligent assistants that provide instant answers to data analytics systems that personalize recommendations, AI has driven a positive revolution in customer service.

    This marriage of advanced technology and financial services has not only improved operational efficiency, but has also raised customer satisfaction, setting a higher standard for the industry as a whole. Artificial intelligence is not just a tool, but a catalyst that has transformed the way customers interact with and perceive banking services, paving the way for a more agile and user-centric financial future.

    Discover how MAIA can be your best ally. Experience firsthand how Artificial Intelligence is a determining factor in the transformation of the Customer Experience in Banking.

    [1] The economic potential of generative AI: The next productivity frontier, McKinzey June 14, 2023

     

  • Intelligent conversational assistants for the internal management of companies. HR Case

    Intelligent conversational assistants for the internal management of companies. HR Case

    How can conversational AI contribute to HR work?

     

    There are more and more technological tools that allow managing talent and internal communications in Human Resources teams, being able to identify and develop the people who lead their teams towards the established organizational goals. Can you imagine all that a Conversational AI or intelligent conversational assistants can do in your company?

    During the last few years, Artificial Intelligence has positioned itself as an indispensable tool to make the internal management of companies more efficient and, as expected, the optimization of human resources management is no exception.

    Intelligent conversational assistants can enhance the efficiency of selection processes, employee care, data analysis, communications, retention and training processes, among others.

    If you want to know more details about Conversational AI you can read our article: What is Conversational AI and how did we get here?

     

    Conversational AI such as MAIA can boost job performance and improve the experience in the corporate environment.

     

    Among the possible uses of conversational AI in HR, the following stand out:

    Recruitment and Selection

    Conversational assistants can assist in reviewing resumes, scheduling interviews, conducting candidate satisfaction surveys and managing candidate communications.

    Employee onboarding

    Conversational AI facilitates the onboarding process for new employees. It provides information on company policies and procedures, delivers necessary documents, and answers common questions that have historically been handled manually by people.

    Training and development

    Intelligent conversational assistants can offer information on training programs, provide development materials, and track employee progression in their professional development.

     

    Benefits and compensation management

    Assistants can answer benefit questions, provide flexible compensation information, assist with enrollment in benefit plans, and track employee applications.

     

    Time management and attendance

    Conversational assistants have the ability to help employees, for example, request vacation time, record hours worked, and resolve questions about time and attendance policies.

    Troubleshooting and frequently asked questions

    Attendees can provide answers to common employee questions, such as company policies, leave request procedures and more.

    Performance evaluation and feedback

    Assistants can help in gathering feedback from employees on their performance evaluations, facilitating the feedback process between employees and supervisors.

    Internal communication

    Attendees can send event reminders, important announcements and personalized messages to employees, improving internal communication.

    Documentary management

    A conversational AI makes it possible to access organizational documents in a simple and structured way without the need for infinite and complex searches. They provide quick, simple and accessible information.

     

    What are the benefits of Conversational AI within HR?

    Intelligent conversational assistants brings many benefits to HR teams, some of the most prominent:

    • Improve employee experience and engagement.
    • Allows for a higher participation and response rate in the team.
    • Time optimization.
    • Improved internal communication.
    • Traceability of interactions to anticipate scenarios.
    • Assists in the detection of behavioral patterns, such as Burnout syndrome.

    We can conclude that conversational AI is currently a tool with great benefits for companies and their teams. By incorporating these innovations, organizations can stay ahead of the curve in an ever-changing business environment.

    Do you want to take the management of your teams and their communications one step further?

    Anticipate with #MAIACognitive.

     

  • Artificial Intelligence arrives to revolutionize customer service efficiency

    Artificial Intelligence arrives to revolutionize customer service efficiency

    Consumer behavior has changed. They come for the product or service, but stay for the customer experience. Consumers want immediacy and quality, but it is often difficult to obtain these two characteristics due to the tight budget for these services.

    The costs of everything have increased and so have labor costs. At that point, you have to think, where can I optimize costs without having to decrease the quality of my service? It is a difficult task, because what differentiates one company from another is not only the price, but also the customer service it provides to its clients. For that reason, companies have to start thinking about differentiation, and yes, technology is the key.

    For the past few years, AI has been all the rage, but not everything that exists is AI. Simple business rules, simple statistics… they call it “Artificial Intelligence”. But Artificial Intelligence (AI) is not that, but the combination of algorithms created with the aim of solving processes that a human being could perform, but perhaps spending more time. For this reason, Artificial Intelligence has become a necessary tool to transform customer service and customer experience. AI can maximize resources, i.e. people, and increase profitability through the efficiencies it generates.

    Savings from Artificial Intelligence application

    AI can be applied in various areas of customer service, from task management to providing customers with products or services that meet their needs. These types of tasks performed by AI allow us to streamline processes and offer more efficient solutions.

    Here are some examples of how AI is generating savings in this field:

    1. Automation of repetitive tasks: One of the biggest savings comes from automating routine tasks. This not only improves customer satisfaction by providing immediate responses, but also frees up customer service agents for more complex tasks. For example, why talk to a person to block your lost card when you can do it yourself by talking to a conversational assistant? MAIA, for example, is able to perform this kind of tasks and many more.
    2. Data analytics: AI can analyze large volumes of data from customer interactions to identify patterns and trends. In this way, companies can understand their customers’ needs and preferences, enabling them to make informed decisions on product, service and process improvements. AI can offer the electricity tariff that best suits the consumption of individuals.
    3. Personalization: AI can personalize the customer experience by providing targeted recommendations based on purchase history and past behavior. This not only increases customer satisfaction, but also drives sales and retention. If you are always traveling abroad in summer, why not offer the best roaming rate?
    4. Reduction of human error: Humans are prone to make mistakes, especially in repetitive tasks due to mental fatigue. AI can help reduce these errors, reducing costs associated with returns, refunds and customer complaints. Human beings get married and sometimes make mistakes, a conversational assistant is always fresh and always does what you have taught him without making a mistake.
    5. Scalability: AI allows companies to scale their customer service operations more efficiently, without the need to hire large numbers of staff. This saves labor costs and ensures consistent customer service at times of high volume. Life is full of unforeseen events… so you can have 2 virtual assistants or 100 when you need them.

    Higher levels of efficiency and satisfaction

    AI is playing a crucial role in transforming the customer experience, generating huge savings for all those companies that implement it.

    Certainly those companies that adopt AI solutions in their customer service strategy are better positioned to deliver exceptional experiences with high levels of efficiency and satisfaction, reducing costs and staying competitive in a constantly evolving market.

    The present and future of customer service is undoubtedly driven by AI.

    Do you want to improve your customers’ experience? Find out how MAIA can help you.

     

  • What is Conversational AI and how did we get here?

    What is Conversational AI and how did we get here?

     

    Conversational AI is a branch of artificial intelligence that simulates human conversations.

    In order to understand what conversational AI is, it is essential to know the concept of Natural Language Processing and how it has evolved to allow us to talk about conversational AI.

    Natural Language Processing

    Natural language processing seeks to teach machines to understand, interpret and generate human language responses. Its beginnings date back to the 1950s, when researchers started working with rule-based approaches and formal grammars to analyze and generate text. However, these systems were very limited as they relied on predefined rules and could not adapt to variations or ambiguities of natural language.

    In order to solve these problems, important advances have been made in recent years, of which we can highlight some key moments.

    Neural Networks

    In the mid-1980s, artificial neural networks applied to NLP began to be used. These were inspired by the structure and functioning of the human brain to develop models capable of learning complex patterns and structures from data. As the availability of large amounts of digitized text data and computational capacity increased, machine learning became an essential tool for the evolution of NLP.

    Deep Learning

    Already at the beginning of the 21st century, NLP underwent a significant transformation thanks to the application of deep algorithms, what we know as Deep Learning. These models improved the ability of systems to understand and generate natural language text, as well as making them more robust and accurate, which is why they began to be applied to tasks such as machine translation, text summarization, text generation or document classification.

    Transformers

    The big change came with the introduction of Transformers in 2017. The most remarkable thing about this architecture is that it contains an attention matrix that evaluates the relationship of each word with all the other words in the sentence, thus taking into account the whole context and allowing to grasp the meaning of the text as a whole.

    Generative Models

    And I’m sure by now you’re wondering at what point we’re going to talk about the famous ChatGPT. Well, the emergence of generative language models such as ChatGPT or LLaMa, introduced in late 2022 and early 2023, are based on an architecture containing several layers of Transformers, which implies that they have hundreds of millions of parameters and also require a corpus with billions of words for training. These models have marked a before and after in AI and are generating strong discussions regarding their impact, as their capabilities in terms of text generation are almost comparable to those of a human.

     

    Once we have traced the evolution of natural language processing, it is easier to understand how we have come to develop what we know today as conversational AI. This is based on models that allow the understanding of language and context, as well as the generation of responses according to the conversation and similar to those that a human would give.

    Would you like to know what a Conversational AI can do for you? We invite you to meet MAIA.

  • Chatbots vs. Conversational Artificial Intelligence

    Chatbots vs. Conversational Artificial Intelligence

    In our busy day, we often have to contact our bank, cell phone provider, or even the gym! In addition, we are often short of time, and therefore want to resolve our queries and formalities as quickly as possible.

    Before making a phone call, we make use (voluntarily or involuntarily) of chat or messaging applications such as WhatsApp. In this way, companies provide us with the information we need without having to talk or interact with a person, and for this they use “chatbots”.

    “Chatbot” is a very common term to name, in a standard way, all the technologies that allow to automate the answers in a chat without the need for human intervention.

    So, when we present MAIA as a conversational Artificial Intelligence, it is normal that we encounter the following questions from some customers:

    Chatbots vs Interligencia Artificial Conversacional

    Is a Chatbot the same as a Conversational AI? What are the differences between one and the other?

    Let’s start with the most important: No, a Chatbot and a Conversational Artificial Intelligence are not the same, but what is the difference?

    Conversational Artificial Intelligences are mainly characterized by capabilities such as:

    Speech recognition.

    Unlike chatbots, conversational AI’s are designed so that, in addition to processing written language, they can identify spoken language.

    Chatbots are usually limited to written channels such as chat or messaging services (WhatsApp, Telegram, etc).

    Natural Language Understanding (NLU).

    A Conversational Artificial Intelligence, it is able to recognize a customer’s requests when he expresses himself in his own words, so it is open to recognize complex requests. Not everyone says the same thing in the same way. For example.

    In the case of chatbots, there is no comprehension capability, the way a customer interacts is through predefined options or a decision tree that guides the conversation through specific topics.

    Dialogue management.

    Conversational AI’s are dialog-oriented. They manage interactions dynamically. They also have the ability to “remember” what they have discussed in previous requests with a customer, pick up on topics, because they manage the context of the entire conversation.

    In contrast, a chatbot manages interactions in a fixed, rule-based way, often guided by menus of options, with no flexibility or ability to go outside the flow. Chatbots, moreover, do not have the ability to remember previous queries to execute or respond to complex requests.

    Natural Language Generation (NLG).

    A conversational AI responds using human and natural language to customer requests and can adapt to the way of communicating in a given situation. While a chatbot gives predefined answers that do not vary or adapt to the context that the customer may have provided.

    Machine Learning (ML).

    The use of Machine Learning allows conversational AI to constantly learn from responses, conversation history and user preferences; this allows to personalize responses and user experience. It also allows the quality of responses to constantly evolve because AI learning is parallel to its operation.

    Technicians take advantage of all the experience acquired by Conversational AI to teach it what to say in new situations not previously identified.

    Chatbots do not learn, their responses are static so they do not allow customizing the user experience; they also need manual programming to keep them updated.

    Most important differences between a Chatbot and a Conversational Artificial Intelligence like MAIA.

    The future… Conversational Artificial Intelligence or Chatbots?

    What is certain is that both Chatbots and Conversational AI’s are here to stay.

    Both allow companies to automate information processes in marketing, sales and after-sales services, mainly thanks to their ability to provide 24/7 attention.

    However, with the recent emergence of Open AI and Chat GPT, and the visibility that is being given to the capabilities provided by Generative AI models, many companies have considered using, or evolving their chatbots, and implementing Conversational AI.

    But what is the main reason? It is undoubtedly to provide a better customer experience, more personalized attention and, above all, to attend to more complex processes in an automated way, resulting in significant savings.

    Do you have any doubts about why you should choose a Conversational AI?

    If so, we’d be happy to talk to you! Shall we talk?