Modern CIS Solutions Powered by AI
Market Trends and Buyers Guide for Utilities
- You are experiencing difficulty navigating through the fast-evolving Utility CIS landscape, which is crowded with vendors claiming AI features.
- You lack insights about which AI features can drive value and minimize existing pain points.
- You lack guidance in evaluating risks associated with AI features offered by modern Utility CIS solutions.
Our Advice
Critical Insight
The marketplace will be full of next generation of Utility CIS solutions offering various AI-powered features. Keeping well-informed about market trends is critical to develop a strong position to effectively navigate the vendor landscape while charting your CIS modernization roadmap.
Impact and Result
Info-Tech’s buyers guide provides practical guide and a tool to empower utility leaders to make well-informed decisions regarding the adoption of AI-powered CIS solutions.
Modern CIS Solutions Powered by AI
Market trends and buyers guide for utilities.
Analyst Perspective
Assess business needs and define return of value up-front.
The conventional focus of a utility customer information system (CIS) centers around the meter-to-cash process, which is a critical element for utilities to recover revenues. As a result, the earlier generations of CIS solutions from vendors emphasized functionalities toward supporting transactional operations. As customer expectations continue to grow, utilities have responded by enhancing their long-term customer relationship through the integrated features offered by modern CIS solutions, covering a comprehensive spectrum of customer-centric functionalities.
The recent surge in AI capabilities, driven by the market breakthrough of generative AI (Gen AI) solutions, has generated great excitement among both utilities and CIS vendors. This excitement also challenges utilities leaders to decide whether to embrace this emerging trend. As we examine current market trends and explore available AI features offered by various CIS vendors, it is important for utilities leaders to carefully consider the potential rewards offered by AI features versus associated risks.
The purpose of this buyers guide is to provide a valuable resource and framework to empower utility leaders to make well-informed decisions regarding the adoption of AI-powered CIS solutions.
Jing Wu
Principal Research Director
Utilities, Industry Practice
Info-Tech Research Group
Executive Summary
Your Challenge
You are experiencing difficulty navigating through the fast-evolving utility CIS landscape which is crowded with vendors claiming AI features.
You lack insights about which AI features can drive value and minimize existing pain points.
You lack guidance in evaluating risks associated with AI features offered by modern utility CIS solutions.
Common Obstacles
Lack of understanding of the maturity of various AI features within the complex CIS ecosystem.
Knowing what specific AI evaluation criteria to add to the existing functional and nonfunctional requirements.
Uncertain about where to start to develop a roadmap to adopt AI-powered capabilities.
Info-Tech's Approach
Introduce a comprehensive market trends and buyers guide for your next CIS modernization initiative.
Provide insights of current and future vendor offerings to determine the timeline for the adoption.
Provide a benefits and risk evaluation tool to guide you through your decision-making process.
Info-Tech Insight
The marketplace will be full of the next generation of utility CIS solutions offering various AI-powered features. Keeping well-informed about market trends is critical to develop a strong position to effectively navigate the vendor landscape while charting your CIS modernization roadmap.
Utilities are facing declines in customer satisfaction
The overall performance of a utility company is often directly correlated with the customer satisfaction rate. Common factors influencing customer satisfaction include service quality, service reliability, pricing, billing and payment processes, communication effectiveness, and overall customer experience.
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U.S. electric utility customer satisfaction is down. |
UK water and wastewater companies overall customer satisfaction continues to fall. |
Australian gas and electricity providers receive |
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Business customers' satisfaction rate has reached an all-time low of 754 points on a 1,000-point scale across the United States according to the 2023 J.D. Power Report. Source: J.D. Power, 2023. |
Pollution incidents and leakage reduction are areas that need accelerated improvements, according to a 2022-2023 performance review from the Water Services Regulation Authority (Ofwat) of England and Wales. Source: Ofwat, 2023. |
Ranked 26th and 27th out of the 28 industries, Australian utilities have lower customer satisfaction ratings than many industries, such as airlines, according to a 2020 Roy Morgan report. Source: Roy Morgan via Statista, 2020. |
Reshape customer experience through AI
Utilities worldwide are exploring ways to improve customer experience (CX) by harnessing the power of people, process, and technology. Particularly, artificial intelligence (AI) stands out as one of the leading technologies to transform customer experience in the utility industries. Across various industries, improving CX is one of the main reasons why organizations adopt AI.
According to a 2021 Global Customer Experience Benchmarking Report, utilities are actively seeking different revenues to enhance customer experiences. In addition to rethinking their operating model and employee strategies, utilities are also investing in AI solutions to differentiate.
Source: NTT via Statista, 2021.
Number One Reason for AI Adoption – Improving Customer Experience
Surveyed respondents are adopting AI to improve customer experience which, as the leading business driver, is more important than operational efficiency and profitability.
Source: Scale, 2023.
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Unlock Sample ResearchContributors
- Kai Chen, Sr. Manager, Planning and Architecture, EPCOR Utilities Inc.
- Ramprakash Ramamoorthy, Head of Zoho Labs and AI Initiatives, Zoho
- Rob Garmaise, VP, AI Research, Info-Tech
- Bill Wong, AI Research Fellow, Info-Tech
- Hong Kwok, Research Advisor, Info-Tech
- Yaz Palanichamy, Senior Advisory Analyst, Info-Tech