塑造2025年客户对话的五大趋势：利用人工智能、云计算与互联生态构建韧性与个性化服务

5 TrendsShaping CustomerConversations in 2025 Building Resilience and Personalization withAI, Cloud, and Connected Ecosystems F O R E W O R D C O N T R I B U T O R S As we look ahead to 2025, it’s clear that the landscape of customer conversations is rapidly evolving. New technologies,shifting customer expectations, and an increasingly complex regulatory environment are converging to create bothchallenges and opportunities for organizations across industries. We developed this report in collaboration with over20 subject matter experts across multiple industries, including healthcare, financial services, and insurance. It aims to Terry BuechnerPrincipal Insurance Specialist at AWS Bob MearaPrincipal Analyst at Celent Sue ClarkeAssociate Principal Analyst at Omdia Rajesh NarayanVice President of Product andUnderwriting, ValueMomentum Ernie CrawfordCEO at Crawford Technologies Trend 1Businesses will need enhanced data quality to support AI initiatives Eileen PotterVice President of Insurance Marketingat Smart Communications Scott DraegerSenior Vice President of ProductMarketing and Vertical Solutions atSmart Communications Trend 2Regulatory challenges and ethical considerations will precede AI implementation Kaspar RoosFounder and CEO at Aspire Trend 3Organizations will prioritize strategic modernization to overcome technical debt Gautam Jit KanwarPresident at BelWo Inc.Alan KatzmanInsurance Industry Principal atPegasystems Jake SloanVice President Global Insurance at Appian Jamie SmithManaging Director, Insurance at Accenture Trend 4Organizations will use data, AI to enhance CX and personalization Simon TindalChief Technology Officer at SmartCommunications Trend 5Companies that prioritize continuous improvement and innovation will increase market share Prashanth KulkarniStrategic Advisor and EnterpriseSolutions in Insurance (Sr. Director)at NTT DATA The world is changing, and the pace of transformation is only accelerating. By understanding and acting on thesetrends, you’ll be positioned to thrive in a customer-first future. Regardless of your industry, the strategies outlined herewill help you build resilience, enhance customer relationships, and ultimately drive growth. We are grateful for the Sumit UppalHead of Digital Strategy & Technology –Financial Services at Capgemini Will LaSalaField CTO at OneSpanChristina LucasGlobal Head, Industry Advisory atGuidewire Thijs WolversSales Director at Nokavision Software B.V. Sincerely, John ZimmererVice President of Healthcare Marketingat Smart Communications Leigh SegallChief Executive Officer, Smart Communications Jim LundyCEO and Founder at Aragon Research Trend 1 Businesses Will Need EnhancedData Quality to Support AI Initiatives As AI continues to gain momentum, leaders across key sectors are prioritizing strong data governanceframeworks and validation processes. High data quality is foundational to successfully implementingAI-based initiatives — and unlocking the potential benefits of AI and advanced analytics across keyindustries. This includes programs, processes, and policies pertaining to AI and machine learning “For customer experiencemanagement and effective customercommunications management, it’s —Gautam Jit Kanwar, President, BelWo Inc. The Foundation of Reliable AI: Data Quality and Governance Data is the key enabler and driver for accelerating digital transformation. For highly regulated industries,data quality and governance are essential to supporting corporate initiatives aimed at improvingefficiency, accuracy, and CX quality. Effectively training the large language models (LLMs) used bygenerative AI (GenAI) requires top-quality input, as do the AI/ML-powered tools that facilitate self- This applies to any industry or organization that relies on customer data not just for communications,but also for operations. Terry Buechner, Principal Insurance Specialist at AWS, explains, “Data qualityis so important to efficient and effective insurance operations, particularly as the need for as well as Robust data governance frameworks, automated validation processes, and AI-driven data management basedon continuous feedback all help to ensure data is clean, standardized, and high-quality. Conversely, lack of data governance can negatively impact data quality and stand in the way of digitaltransformation. According to Bob Meara, Principal Analyst at Celent, “For banks, our view is that the number The Link Between Consumer Trust and Data Accuracy As the majority of the data that businesses rely on comes directly from the consumers they serve, trust is missioncritical — after all, you’re asking them to hand over their most sensitive personal information. It’s important thatthe processes you use to capture client data ensure accuracy and completeness, flowing into a data lake or Smart Communications’ 2024 Financial Services GlobalBenchmark Reporthighlighted the importance of clearand accurate communications in building