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Here’s How to Integrate AI Without Losing the Human Connection

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Here’s How to Integrate AI Without Losing the Human Connection


Artificial intelligence (AI) is seemingly taking over a lot of human jobs, including manufacturing, some aspects of medicine, and customer service. As AI becomes more and more sophisticated, many are naturally concerned that it will replace all human jobs.

Businesses staffed entirely by AI machines isn’t a likely outcome, however. While pop culture may have us fearing the worst, AI’s use is more to enhance and augment human capabilities — not take their place.

Digital tools are more responsive, accessible, and cost-effective than ever. AI will change the way we work but not the way we think.

In customer service, AI takes on the mundane, repetitive, high-volume, and time-sensitive work that human workforces simply can’t manage, leaving them to do what only humans can do – provide the human connection.

How Is AI Used in Customer Service?

AI is a large branch of computer science that focuses on smart machines that are capable of performing tasks that usually require human intelligence. It allows machines to model and, in some cases, improve upon what the human mind is capable of.

Most of the AI we encounter falls into one of two categories: narrow AI and general AI. Narrow AI is used for smartphones, tablets, and computers that we use every day, such as Alexa voice recognition technology.

General AI is more advanced. For most of us, general AI is closer to the high-tech robots we see in movies and television shows.

Customer service AI is narrow AI, such as data analytics, self-service tools, and chatbots, but there are many other applications. Though some form of AI in customer service has been around for decades, now, it offers incredible opportunities for businesses to provide a higher level of service without adding to costs or staff.

Here are some examples of how AI can be used in customer service.

Chatbots

Chatbots are among the most widely used and familiar applications of AI in customer service. This software mimics natural human interactions in customer support chat windows to help customers find solutions to their problems while still feeling like a natural conversation.

Many businesses operate in different time zones, sometimes different countries and languages, and it can be challenging to provide prompt, thorough support for these customers. Chatbots are available around the clock, provide answers in real-time, and can speak multiple languages for international customers.

For example, our legal clients are busy people — which is why they need law enforcement transcription services to reduce their workload. If they have a problem or question, they don’t want to wait on the phone for a customer service representative, especially if it’s a simple and straightforward issue. Chatbots can not only answer questions but can direct customers to resources like FAQs or forums to find help independently. Law enforcement also operates 24/7, so this industry needs customer service that can provide help at any time they need it, rather than during normal business hours only.

Self-Service Tools

Customers want self-service solutions. According to the NICE 2022 Digital-First Customer Experience Report, 81% of consumers want self-service options for speed and convenience when dealing with their problems. They want to find solutions at the time they need them — instead of jumping through hoops to get help.

Fortunately, a lot of customer service requests and inquiries can be addressed with technology, rather than human representatives. Self-service solutions like community forums, FAQ pages, and learning resources with filters help customers find the information they need quickly and easily. Chatbots can also be used to direct customers to relevant resources, rather than having them waste time searching on their own.

Natural Language Processing

Natural language processing (NLP) is a component of AI that allows a computer program to understand written and spoken human language. NLP has widespread potential in customer service to enhance the experience a customer has when interacting with chatbots, phone recordings, and emails. It can also understand voice requests to help customers find the information they need.

In addition to direct customer assistance, NLP can analyze the data collected through customer service efforts to provide in-depth insights to improve the customer service experience. Because AI can interact with thousands of customers at once, it gathers a high volume of data that humans can’t match while also saving company resources.

AI Training

AI in customer service helps with employees and customers as well as employees in training. Typically, customer service representatives are trained by one person, then put on calls to use their training. With AI, new and existing employees can continuously learn and grow, without an added burden on the manager.

Conversational AI can be used to train employees in customer service with simulated conversations outlining virtually limitless scenarios that come up in customer service. Otherwise, employees may have to wait until unique situations arise with real customers for the learning experience. They also receive feedback on how they handled the interaction, learning from situations that are more like the real world.

Analyzing Customer Data

Machine learning, another component of AI, is a staple in virtually every business to analyze customer and business data. The sheer volume of data that businesses collect now is challenging, if not impossible, for humans to analyze quickly for rapid insights. Machine learning analyzes thousands of interactions to ascertain behavioral patterns and preferences.

How does this help human customer service representatives? Instead of providing standard answers and solutions, machine learning can offer in-depth insights for more personalized service and a better customer service experience.

Benefits of AI in Customer Service

Providing the level of customer service that customers are seeking is challenging, especially for large businesses but here are some ways that AI helps:

Streamlined Workflows

The customer service department can get incredibly busy. Customer service representatives are burdened by a high volume of calls from customers, often with long wait times, leading customers to hang up or get frustrated before they even broach their issues.

AI streamlines the customer service workflow to relieve the burden on human customer service representatives. Simple questions and issues can be addressed by chatbots, either directly or by leading the customer to self-service tools. These customers are no longer calling or emailing, tying up customer service representatives. They can then focus on the more complex issues that customers have, ones that require empathy and understanding.

24/7 Support

Many businesses operate on a national or international scale. If they need help, they want to be able to reach the customer service center at the time that works best for them – not necessarily during normal business hours on weekdays (when they may be working themselves).

AI provides this higher level of service by providing “customer service agents” to customers at any time, day or night, and on any day of the week. Customers can access chatbots or self-service options whenever they need them, and businesses can offer these options without hiring 24/7 staff.

Exceptional Customer Service

Customer service is a differentiator for brands that have a lot of competitors. When customers know they can count on a positive customer service experience if they have a problem, they’re more likely to make a purchase in the future.

Providing that level of experience is challenging, however. AI can help businesses provide better customer service using data analysis. As these tools become more sophisticated, they provide more information about customer behaviors, purchases, and interests. Customer service representatives can use this information to offer personalized solutions and offer to the customer. AI also offers 24/7 support, fast response times, and self-service solutions that customers prefer.

Better Lead Generation

Getting a customer to make a purchase takes a lot of work, but several things can go awry before that purchase is complete. AI creates a smooth, consistent buying process that helps customers find the most relevant products – even upselling or cross-selling  — and leads them to make a purchase. It can also anticipate any problems that may prevent their purchase, even before the customer is aware of them, removing barriers in the purchasing process.

For example, our transcription services cover a lot of industries, including academic transcription services. AI can direct our customers to the services that are most relevant, saving them time and making the process quick and easy.

Cost-Effectiveness

According to research from IBM, businesses spend over $1.3 trillion on customer service calls globally. This spending is allocated to over 265 billion customer service calls that take place each year. AI can not only relieve some of that burden but speed up response times and free customer service representatives to handle more complex issues.

AI, like chatbots, is useful for routine questions, which are the bulk of customer service inquiries. Customers get the fast answers they want, at any time and from anywhere, and customer service representatives have time to speak to customers directly when their issues are more complicated and require human interaction.

Reduced Burnout

Customer service can be a stressful job. No human being can work 24/7, either, and many businesses lack the resources to provide 24/7 multilingual staff to support all their customer calls. To make matters worse, customers who call in frustrated may only add to the stress and increase the wait times.

AI can work around the clock, ensuring that customers have support options on weekends or after hours. Customer service representatives deal only with the calls that require a human touch, empowering them to deliver a higher level of service and reducing burnout and fatigue in the process.

Collaboration Between Humans and AI

We may fear Ai replacing human workers, but it’s not enough to replace the creativity, empathy, and understanding that humans provide – especially in a customer service capacity. AI isn’t a threat to the future of work but an important improvement that makes human workers even more effective.

Enhancing Decision-Making and Creativity

One of AI’s advantages over humans is that it can analyze information and make decisions much faster, and with fewer errors, than humans. Customer service representatives can use this effectively to provide in-depth information to customers during service calls and offer personalized and targeted solutions.

Automating Mundane Tasks

Regardless of industry, AI is being used successfully to replace humans on mundane, repetitive tasks. In customer service, AI chatbots can address simple questions or direct customers to specific answers, freeing human workers to work solely on interactions that require a live person. AI can also accomplish these tasks at a much higher volume than humans, allowing more customers to be served in a shorter period of time.

Collaborating on Tasks

Collaborative robots, also known as cobots, are a new AI solution that combines machines and humans to automate work and support human staff. These robots are adaptable, safe, and cost-effective, supporting automation while sharing workspaces with humans instead of replacing them. As a result, customer service representatives are free to focus on the tasks that only they can do, delegating or automating the rest to AI.

For example, our legal transcription (dittotranscripts dotcom) customers have a lot of work to do and not enough time to do it, which is why they outsource legal transcription. If they have a problem, they don’t have time to send emails and wait for replies or sit on hold waiting for a representative. Offering self-service options lets these busy customers get fast answers and solutions to their problems, no matter the time of day. If they still need help, customer service representatives are available — since they’re not burdened with a high volume of customer service calls for simple concerns.

Elevate Customer Service with AI

As AI gets more sophisticated and accessible, it will gain widespread adoption in all types of industries. It’s not going anywhere, but we don’t need to fear it replacing valuable human jobs like customer service. Instead, it can enhance the customer service experience by providing in-depth insights and practical answers that support customers whenever they need assistance. By collaborating, AI and humans allow customer service representatives to handle the work only humans can do.

Featured Image Credit: Pexels; Thank You!

 

Ben Walker

CEO at Ditto Transcripts

Ben Walker is a CEO, entrepreneur, and visionary leader that enjoys helping others become successful in business and in life. Ben’s company, Ditto Transcripts, provides user-friendly and cost-effective transcription services for the medical, legal, law enforcement, and financial industries for organizations all over the world. Ben is a sought after thought leader and has made contributions to publications like Entrepreneur Magazine, Inc, Forbes, and the Associated Press.
Follow Ben’s Tweets: @benjaminkwalker



Politics

Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Politics

Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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Politics

UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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