Tag: artificial intelligence

Enhancing Customer Experience through AI-driven CX: Bringing Innovation and Human Connection Together | Blog

Read on to explore how AI is revolutionizing customer experience (CX) in today’s fast-paced digital landscape. In this expert analysis, you will learn how AI-driven solutions enhance customer journeys, personalize interactions, and streamline operations. Discover the pivotal role of human talent in ensuring the success of AI-driven CX and how businesses can harness these innovations to create seamless, customer-centric experiences. Reach out to us directly to discuss this topic further.

In today’s fast-paced digital landscape, customer experience (CX) stands at the forefront of business success. Companies are increasingly turning to AI to revolutionize their customer interactions, streamline operations, and provide a seamless journey from start to finish. AI-driven CX is not just a buzzword; it’s a game-changer, offering a host of benefits to both businesses and their customers alike. In this blog, we’ll delve into how customers stand to benefit from AI in their journey and highlight the pivotal role of human talent in ensuring the success of AI-driven CX.

Enhancing the customer journey with AI

Imagine a seamless, personalized experience tailored precisely to your preferences and needs, available at your fingertips. That’s the promise of AI-driven CX. From personalized product recommendations to proactive customer support, AI empowers businesses to anticipate and meet customer expectations like never before.

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Elevated experiences: hyper-personalization for unparalleled connections

One of AI’s biggest benefits for CX is using data to achieve true personalization at scale. AI can analyze a company’s vast pools of customer data – from transactions to browsing behaviors to communication histories – to build rich customer profiles. It can then surface insights to deliver experiences tailored to each individual’s preferences, needs, and contexts.

For customers, this enables a new level of relevance from the brand interactions they receive. AI-powered recommendation engines, such as those from Netflix, Spotify, and Amazon, ensure customers always see the most fitting content or product suggestions.

For businesses, envisioning how AI-powered recommendation engines could work in their own context unlocks a new level of relevance in brand interactions. AI algorithms can ensure that customers receive personalized recommendations for support resources or solutions tailored to their specific needs and preferences. Moreover, AI can personalize messaging tones, channels, and cadences for outreach, creating smoother, more engaging experiences for customers. By leveraging AI in this way, customer service teams can deliver proactive and tailored support that addresses customer needs efficiently and enhances satisfaction.

Anticipating needs: proactive care redefining customer support

AI opens up powerful new possibilities for proactive customer care. With machine learning models analyzing data patterns, businesses can anticipate customers’ likely future needs or issues and be proactive about resolving them. This benefits customers by allowing problems to be addressed before any major disruption or frustration occurs.

For instance, a telecom company notices an increase in calls related to a network outage in a specific area. Instead of waiting for frustrated customers to flood the lines with complaints, the contact center proactively sends out automated notifications to affected customers, informing them of the issue and providing estimated resolution times. Additionally, the system identifies high-priority customers, such as those with critical business needs or medical emergencies, and prioritizes their inquiries for immediate resolution. Another example is when an insurance provider utilizes proactive outreach strategies, such as sending notifications when insurance coverage is expiring or subscriptions are ending, along with discounts or offers for renewals.

Efficiency amplified: faster, smoother, better resolution times

When customers do need to directly engage a brand for support, AI can accelerate resolution times and reduce frustration. Conversational AI assistants are becoming smarter at understanding complex language to quickly identify the true intent behind customers’ requests. From there, AI can directly handle simpler queries, tasks, or transactions through self-service.

For instance, an AI assistant could autonomously resolve a customer asking to return a parcel by walking through the process and initiating a refund. For more complex cases, AI can automatically route the conversation to the right human agent or department for seamless escalation.

This AI-powered triage and assistance cuts down tedious back-and-forth, reducing resolution times and customer effort. When human employees are looped in, they have full context to focus on providing a tailored, speedy resolution.

The human touch: why human talent matters in AI-driven CX

While AI brings transformative capabilities, human agents remain vital for delivering empathetic, personalized customer experiences – especially for complex, emotional situations. AI can augment and empower human workers, rather than replace them. Here’s why human talent is crucial in AI-driven CX:

Empathy and emotional intelligence

AI may excel at analyzing data and predicting behavior, but it lacks human empathy and emotional intelligence. Empathetic human interactions are essential, especially in sensitive situations or complex inquiries where understanding and compassion are paramount. Human agents can empathize with customers, actively listen to their concerns, and provide personalized solutions that resonate on an emotional level.

Complex problem solving

While AI can handle routine queries and tasks with efficiency, complex issues often require human intervention. Human agents possess critical thinking skills and domain expertise to navigate intricate problems, adapting to unique situations and finding creative solutions. By combining AI’s automation capabilities with human problem-solving skills, businesses can deliver comprehensive support that addresses the full spectrum of customer needs.

Building trust and loyalty

Trust is the foundation of customer relationships, and human interactions play a vital role in fostering trust and loyalty. Customers value authentic connections with human representatives who demonstrate understanding, sincerity, and integrity. While AI can streamline processes and deliver personalized experiences, it’s the human touch that cultivates meaningful connections and builds long-term loyalty.

Continuous improvement

Human feedback is irreplicable for refining AI algorithms and enhancing the customer experience. Human agents act as the last checkpoint before messages reach customers, ensuring authenticity and relevance. Moreover, with AI’s potential to hallucinate, skilled agents play a crucial role in validating AI-generated insights and enhancing the overall customer experience. By fostering collaboration between humans and AI, businesses can achieve continuous improvement in their customer operations and stay ahead in a competitive market.

Conclusion: the future of customer experience (CX)

In the dynamic realm of CX, the fusion of AI innovation and human expertise emerges as a cornerstone for success. As businesses embrace AI-driven solutions to streamline operations and personalize interactions, they can unlock unprecedented levels of efficiency and customer satisfaction. However, amidst these technological advancements, the pivotal role of human agents cannot be overlooked. With their empathy, creativity, critical thinking, and problem-solving abilities, human agents add an indispensable touch to customer interactions, fostering trust and loyalty in an increasingly digital landscape. By striking the right balance between AI-driven innovation and human connection, businesses can navigate the complexities of CX, delivering seamless experiences that resonate with customers and propel their brands to new heights of success.

For more details on customer experience and AI reach out to Rishav Kumar, [email protected], or Aishwarya Barjatya, [email protected].

Learn more about how to utilize AI and its latest iteration, generative AI, for anticipating CX needs in the LinkedIn Live session, Leveraging AI for CX.

Leveraging AI for CX | LinkedIn Live

LINKEDIN LIVE

Leveraging AI for CX

Watch this event on LinkedIn which was delivered live on Wednesday, June 5 2024

To meet evolving customer expectations, businesses are seeking to develop artificial intelligence (AI) tools to enhance their customer experiences. From personalizing experiences to providing in-depth analytics, the potential for AI to transform CX and its management is profound. 🚀

Watch this LinkedIn Live discussion with Everest Group’s Nishan Krishan, Practice Director, and Ashish Sehdev, Vice President, to learn about how to utilize AI and its latest iteration, generative AI, for anticipating CX needs, creating adaptive strategies, and developing unforgettable CX. 💡

During this engaging LinkedIn Live, we discussed:

✅ The use cases enabled by AI in CX 🤖
✅ The RoI and productivity gains enabled by AI in CX
✅ Generative AI and its disruptive potential for CX

Krishan Nisha gray square 1
Practice Director
Everest Group
Sehdev Ashish gray square
Vice President
Everest Group
Kumar Santhosh
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Decoding the EU AI Act: What it Means for Financial Services Firms | Blog

How will the EU AI Act impact the financial services sector, and how should enterprises and service providers structure their compliance activities? Read on to learn about what this new legislation means for financial services firms looking to implement AI tools, or get in touch to understand the direct impact on your specific business.

In recent years, the rapid advancements in artificial intelligence — in particular, generative AI — have revolutionized various sectors, including financial services. Technology giants such as Microsoft, Google, Amazon, and Meta have heavily invested in developing AI models and tools. However, this unprecedented growth has also raised concerns about the potential risks associated with the unchecked use of AI, prompting the need for regulations to ensure the responsible development and deployment of these powerful technologies.

Recognizing the urgency of the situation, the European Union has taken a proactive step by introducing the AI Act, a pioneering piece of legislation that aims to establish a comprehensive framework for the development and use of trustworthy AI systems. The Act adopts a risk-based approach, categorizing AI systems into four distinct levels:

  • Unacceptable risk – Systems deemed a serious threat, such as predictive policing, real-time biometric identification systems, and social scoring and ranking are banned
  • High-risk – Systems with potential to harm people or fundamental rights, such as AI-powered credit assessments, require strict adherence to new rules regarding risk management, data training, transparency, cybersecurity, and testing. These systems need to register with a central EU database before distribution
  • Limited risk – Systems posing minimal risk, such as chatbots, need to comply with “limited transparency obligations,” such as labeling AI-generated content
  • Low or minimal risk – While not mandated, the Act encourages providers to follow a code of conduct similar to high-risk systems for market conformity

The AI Act and financial services

The financial services industry heavily relies on AI, from personalized banking experiences to fraud detection. The high-risk applications especially require financial institutions to prioritize the following:

  • Continuous risk management – Focus on health, safety, and rights throughout the AI lifecycle, including regular updates, documentation, and stakeholder engagement
  • Comprehensible documentation – Maintain clear, up-to-date technical documentation for high-risk systems, including characteristics, algorithms, data processes, risk management plans, and automatic event logging
  • Human oversight and transparency – Maintain human oversight throughout the AI lifecycle and ensure clear and understandable explanations of AI decisions
  • Rigorous governance – Implement robust governance practices to prevent discrimination and ensure compliance with data protection laws
  • Fundamental rights impact assessment – Conduct thorough assessments to identify and mitigate potential risks to fundamental rights
  • Data quality and bias detection – Ensure training and testing datasets are representative, accurate, and free of bias to prevent adverse impacts
  • System performance and security – Ensure consistent performance, accuracy, robustness, and cybersecurity throughout the lifecycle of high-risk AI systems

To align with the EU AI Act, enterprises must take a structured approach. First, they should develop a comprehensive compliance framework to manage AI risks, ensure adherence to the Act, and implement risk mitigation strategies. Next, they need to take inventory of existing AI assets like models, tools, and systems, classifying each into the four risk categories outlined by the Act. Crucially, a cross-functional team should be formed to oversee AI risk management, drive compliance efforts, and execute mitigation plans across the organization. By taking these steps, enterprises can future-proof their AI initiatives while upholding the standards set forth by the landmark regulation.

Final Everest Group Decoding the EU AI Act What it means for financial services
Opportunities for service providers

  • AI governance expertise – Service providers can offer expertise in building and implementing AI governance frameworks that comply with the EU AI Act. This includes developing policies, procedures, and tools for responsible AI development and deployment
  • Data management solutions – Service providers can assist financial institutions in managing their data effectively for AI purposes. This includes data cleaning, labeling, and ensuring data quality and compliance
  • Large Language Model operations (LLMops) – As financial institutions explore the use of Large Language Models (LLMs), service providers can provide expertise in LLMOps, which encompasses the processes for deploying, managing, and monitoring LLMs
  • Use case classification & risk management – Service providers can help financial institutions classify their AI use cases according to the EU AI Act’s risk framework, and develop appropriate risk management strategies
  • Quality Management System (QMS) – Implement a robust QMS to ensure the AI systems consistently meet the Act’s requirements and other emerging regulatory standards

The road ahead

As the AI Act progresses through the legislative process, financial institutions and service providers must proactively prepare for the upcoming changes. This includes conducting AI asset inventories, classifying AI systems based on risk levels, assigning responsibility for compliance, and establishing robust frameworks for AI risk management. Service providers will play a crucial role in supporting financial institutions in their compliance efforts.

To learn more about the EU AI Act and how to achieve compliance with the regulations, contact Ronak Doshi, [email protected], Kriti Seth, [email protected] and Laqshay Gupta, [email protected]. Understand how we can assist in managing AI implementation and compliance, or download our report on revolutionizing BFSI workflows using Gen AI.

The Rise of AI Developers – How Devin and other Autonomous AI Agents will Reshape Software Development | Blog

Cognition AI’s Devin and other autonomous AI agents are poised to revolutionize software development. Read on to explore Devin’s features and benefits, the impact of AI developers on IT services delivery, and the challenges that accome with moving into the age of intelligent software development. Reach out to learn more about this topic.

The world of software development is on the cusp of a paradigm shift. Cognition AI’s launch of Devin, the first fully autonomous AI software engineer, marks a significant leap forward in AI capabilities. Devin and other AI agents promise to transform how software is built and profoundly impact the IT services industry. Let’s explore this further.

What can Devin do?

Devin is different from your average coding assistant. This AI agent can independently plan, execute, and complete complex software engineering tasks. For example, if Devin were given a problem statement to build a website with specific functionalities, it would:

Craft a step-by-step plan: Break the project down into manageable tasks, considering factors like technology stack, user interface design, and API integrations.

Develop the software: Write code, handle errors, and build the core functionality using tools familiar to human engineers, such as code editors and debuggers.

Deploy the solution: Deploy the website it built on a server and ensure user accessibility.

This level of autonomy is groundbreaking. While Devin might still require human oversight for complex projects or strategic decisions, its ability to handle entire workflows independently opens a new frontier in software development.

What does it mean for software development?

The advent of Devin AI marks a significant leap in the software development process. This transformative technology heralds a future where AI can undertake intricate coding tasks, driving numerous benefits.

Below are some potential benefits of AI developers:

Increased Productivity: Repetitive tasks like coding basic functionalities or fixing bugs can be automated, freeing human developers for more creative and strategic work.

Reduced Development Time: AI handling of routine tasks can significantly shorten development cycles, allowing companies to bring products to market faster.

Democratization of Development: AI tools could empower non-programmers to build basic applications, fostering innovation and citizen development.

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Concerns with AI developers

However, it is important to remember that Devin AI doesn’t have all the answers yet, and many unknowns must be addressed. Below are a few concerns surrounding Devin AI:

Infrastructure Requirements: The infrastructure required to run Devin may prove to be a limiting factor for its adoption.

Security and Compliance: Security, governance, and regulatory compliance factors can significantly influence the applicability of Devin across use cases.

Pricing Uncertainty: Cognition has not released any information about the potential price points for Devin AI.

What does it mean for the IT services industry?

The rise of AI developers presents both challenges and opportunities for the IT services industry that will affect the following dimensions:

Shifting Skillsets: Demand for traditional coding skills may decrease as AI handles routine tasks. However, the need for skilled professionals who can manage AI tools, design complex systems, and ensure security will rise.

Evolving Service Offerings: IT service providers must adapt their offerings to leverage AI development tools. This could involve offering AI-powered development platforms, AI integration services, and expertise in managing human-AI collaboration.

Focus on Consulting and Strategy: As the technical aspects become less labor-intensive, IT service providers can focus on higher-value services like consulting, project management, and providing strategic guidance on AI adoption.

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The road ahead

Devin’s arrival is just the beginning. As AI capabilities continue to advance, even more sophisticated development tools and agents will emerge. Leading IT services providers that embrace this change, invest in workforce reskilling, and leverage AI effectively will be well-positioned to thrive in the age of intelligent software development.

This shift will not be without its challenges. Ethical considerations about AI bias and potential job displacement need to be addressed. However, the potential benefits of AI development are undeniable. As we move forward, embracing collaboration and fostering a human-AI partnership will be crucial to unlocking the full potential of this exciting new frontier.

To share your thoughts and discuss our research on the future of software development and the rise of AI developers, please contact [email protected] or [email protected].

Watch the webinar, AI-driven Sourcing: Discover the Best-in-Class Features in Autonomous Sourcing Tools, for insights into the complex technology landscape of autonomous sourcing tools and the various functionalities autonomous sourcing tools offer across the sourcing workflow.

Gen AI Unhyped: Where is it Working and How to Plan for Success | LinkedIn Live

Linkedin Live

Gen AI Unhyped: Where is it Working and How to Plan for Success

View the event on LinkedIn, which was delivered live on Tuesday, April 3, 2024.

While generative AI (gen AI) seems to be the predominant theme of the time, there is still a lack of clarity regarding where the technology works best and where the primary developments are occurring. 🧠💻

Watch this LinkedIn Live where our expert’s explored tangible, real-world gen AI applications, addressed challenges for practical implementation, and discovered key insights to assist in staying ahead in harnessing the potential of gen AI for your business. 🚀

During this session, we addressed the following questions:

✅ What is the current on-the-ground adoption of gen AI among enterprises?
✅ Which enterprise areas and functions are seeing the highest level of gen AI activity and interest?
✅ What are the key challenges and risks associated with gen AI, and what are the potential solutions to overcome them?
✅ How can organizations become gen AI-ready across talent, culture, and technology?

Gupta Vishal
Partner
Everest Group
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Vice President
Everest Group
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Ketan Singh
Staff Software Engineer (Tech Lead)
Meta
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CPOs: Do More with Less in APAC through Gen AI, Innovation, and Rate Cuts | LinkedIn Live

LinkedIn Live

CPOs: Do More with Less in APAC through Gen AI, Innovation, and Rate Cuts

View the event on LinkedIn, which was delivered live on Thursday, March 21, 2024.

2024’s CPOs, senior procurement, and VMO leaders in the Asia-Pacific region are seeking to accelerate revenue growth while keeping rising costs at bay. In other words, they want to do more with less. 
 

To achieve this, they are focusing on adopting modern technologies such as generative AI (gen AI) to drive productivity, ensuring supplier innovation moves the needle, rebalancing their sourcing portfolios, and driving sustainable growth through optimized processes. 🛠️🔍

Watch this engaging APAC-focused LinkedIn Live discussion where our analysts and procurement veterans explored sourcing and supplier strategies that can drive accelerated revenue growth and enhance cost optimization. 

During this session, we explored:

✅ CPO and procurement leaders’ priorities in 2024 🎯
✅ How technology modernization (e.g., through gen AI) can drive productivity and accelerate revenue growth 🚀
The outlook for pricing in 2024 in APAC and the best-in-class negotiation and contracting tactics that procurement and category management leaders are using 💰
✅ How sourcing and supplier management leaders are driving innovation from their strategic suppliers

Meet the Presenters

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Head of Procurement, India
Philip Morris International
Malhotra_Bhanushee
Practice Director
Everest Group
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Head of APAC Strategic Sourcing & Global Buying Center
Uber
Sharma Abhishek 1
Partner
Everest Group

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