A contribution by Sophie Hundertmark.
Sophie Hundertmark is an expert in the practical use of artificial intelligence with a focus on chatbots, AI strategies and responsible technology integration. She is a researcher and lecturer at the Lucerne University of Applied Sciences and Arts and is currently writing her dissertation in the field of Conversational AI at the University of Fribourg. As a consultant, she supports companies, administrations and educational institutions in the introduction of effective AI solutions. Find out more about Sophie Hundertmark on Linkedin.
The way in which companies interact with their customers and make information accessible is undergoing fundamental change. With the advent of advanced AI-powered tools such as ChatGPT, Perplexity and Gemini,AI chat management is no longer just a technological gimmick or an addition to existing marketing efforts. It has become a strategic necessity that must be firmly anchored in the core strategy of every company. This development goes far beyond traditional search engine optimization (SEO) and establishes a paradigm shift: from pure keyword optimization to holistic contextualization and relationship building. Companies must fundamentally adapt their structures, skills and processes in order to fully exploit the potential of AI-supported chats and operate successfully in the new era of search.
Required skills and new roles
The successful implementation of AI chat management requires specific skills and an adjustment of the distribution of roles.
Key competencies
- Analytical skills: To interpret data from AI interactions, measure performance and identify optimization potential.
- Strategic thinking: To anchor AI chat management as an integral part of the overall corporate strategy and define long-term goals.
- Communication skills: The ability to formulate clear messages, ensure consistent brand communication and prepare content for machines and people at the same time.
- Technical understanding: A basic understanding of AI models, how they work and the associated technical requirements.
- Creativity and storytelling: To develop content that is not only informative but also appealing and builds trust.
- Empathy and customer understanding: A deep understanding of customers’ needs and issues in order to offer relevant solutions.
- Change management: The ability to accompany organizational changes and to inspire employees for the new requirements.
New castors and adapted profiles
Companies may need to create new roles or adapt existing profiles to meet the requirements of AI chat management:
- AI Chat Manager (Strategic): This role is responsible for developing and implementing the overarching AI Chat management strategy. This includes defining goals, allocating budgets, selecting the right AI tools and ensuring integration into the overall corporate communication. They act as an interface between marketing, PR, IT and top management.
- Prompt Engineer (Technical-Creative): Specialists who formulate queries (prompts) in such a way that AI models provide the desired, precise and relevant answers. They understand the intricacies of AI language models and can significantly influence the quality of the information output through targeted prompt optimization.
- AI Content Strategist (Content-Strategic): Responsible for conceptualizing and driving content to be deemed relevant, trustworthy and helpful by Large Language Models (LLMs). They work closely with the PR and social media teams to ensure that the content is engaging for the human audience and conveys the brand message consistently.
- Digital Reputation Manager (trust-building): This role focuses on building and maintaining the company’s digital reputation in the context of AI tools. They monitor mentions, citations and recommendations in AI-generated responses and develop strategies to actively shape digital perception.
- AI Data Analyst (Analytical): Specialists who measure the performance of AI chats, analyze data from user interactions and identify optimization potential. They develop metrics and reports that provide information on the effectiveness of AI chat management strategies.
- UX/UI Designer (user-centered): Although AI chats are often text-based, usability is key. This role ensures that interaction with the chatbots is intuitive, efficient and pleasant.
- Legal expert for AI communication (compliance): As the use of AI tools increases, issues of data protection, copyright and liability become more relevant. This role ensures that all AI chat management strategies comply with the legal framework.
The role of trust and relationship management
At a time when specialist information can be easily disseminated and duplicated by AI systems, targeted and reliable communication plays a crucial role.
Trust as a pillar of success
Alongside relevance and resonance, trust is one of the most important pillars for success in the era of AI search. AI models are cleverly designed; they look for correlations and try to understand the user’s intention – the “job to be done”. Content that is not only thematically appropriate, but also comprehensive and with added value, is easier to find. A high level of trustworthiness is crucial here. Companies must not only present themselves as experts in their field, but also appear likeable and appealing.
Active relationship management with stakeholders
In order to build trust, active relationship management with various stakeholders is of great importance:
- Customers: A deep understanding of customer language and their needs is essential. If companies can answer their customers’ questions, they position themselves as a trustworthy source of information. Interaction and feedback are crucial here in order to create resonance and contribute to building trust.
- Opinion leaders and influencers: A high response is achieved when content is quoted, recommended and discussed by others. Integrating the brand into external content or establishing it as an opinion leader increases credibility.
- Press and media: Well-placed press releases, quotes and mentions on credible websites increase the likelihood of being considered by AI tools. PR agencies are the interface for AI communication here.
- Industry peers and partners: Collaborations and joint initiatives can strengthen reputation and increase visibility in AI-based answers.
- Employees: A customer-oriented culture within the company strengthens the understanding of customer needs and promotes the creation of relevant content.
Facts instead of fakes
In times when misinformation and manipulated content are on the rise, PR and social media agencies as well as in-house communications teams are helping to make high-quality, verifiable content visible and build authentic authority. This is an important contribution to avoiding misinformation in AI-based responses and to securing trust in the long term. In the long term, simulating reach and visibility through fake profiles and manipulated content undermines trust and damages reputation.
Organizational anchoring and processes
Adapting to the new search landscape requires a holistic change in corporate culture and processes.
Customer-oriented culture
Thinking in terms of customer experience management (CX) and understanding the customer’s “job to be done” must take center stage. Companies must always ask themselves: What problem am I solving for the customer?
Multi-experience approach
Your content must be available in the right tone of voice across different channels in order to map the customer journey holistically. This requires avoiding silo thinking (e.g. marketing vs. sales vs. service) and instead considering which content is needed in which phase of the customer journey. The service sector in particular offers considerable potential for relevant and findable content, such as service videos.
Continuous adaptation and monitoring
The exact metrics for success in AI search are still under development. It is therefore crucial to define relevant KPIs and continuously monitor market developments and adapt strategies. This requires regular meetings in which these adjustments are discussed and decided.
KPIs and meetings for AI chat management
The implementation and success of AI chat management strategies must be made measurable.
Extended key performance indicators (KPIs)
To measure the success of AI chat management, specific indicators that target presence and recommendation in third-party AI chatbots are crucial:
- Number of mentions and recommendations in AI tools: This is the central metric. It measures how often company content is quoted, linked or directly referenced in responses by large AI chatbots such as ChatGPT or Perplexity as a relevant source of information.
- Quality of the AI-generated answers: It is important to assess how precise and complete the answers generated by the AI systems are when they are based on company information. Are the key messages reproduced correctly and is the information in the right context?
- Visibility in the “knowledge cutoff” of AI models: Since AI models often have a “knowledge cutoff”, it is crucial to know if and how your content is visible after this cutoff date, especially for breaking news and information.
- Trust score of the AI recommendations: This measures how trustworthy users perceive the information given by AI chatbots about the company. This can be determined through sentiment analyses of user reactions to AI responses or through surveys.
- Proportion of relevant and resonating content: This KPI measures how much of the content provided by the company is rated as “relevant, trustworthy and helpful” by AI models. Resonance is indicated by the frequency with which the content is cited, recommended and discussed by others.
- Increase in organic reach through AI: Measures the increase in traffic or interactions directly attributable to recommendations or information from AI chats.
- Positioning as a thought leader in AI responses: This assesses how often the company or its experts are highlighted as an authority or source of deep knowledge on complex topics by AI systems
New meeting structures and measures
- “AI Steering Committee”: A strategic committee at management level that defines the overall strategy for AI chat management, allocates budgets and monitors progress. The findings from the study on the future of search, which shows how search behavior is changing as a result of AI tools, are also discussed here.
- Regular “Content & AI Syncs”: Operational meetings between content creators, PR teams, social media managers and AI experts to optimize content and test new approaches.
- Workshops on “Trust & Reputation in the AI Era”: Regular training for all relevant employees to raise awareness of the importance of trust and reputation in AI-supported search.
- Definition of “AI readiness” standards: Establishment of clear guidelines and checklists for the creation of content that is optimally prepared for AI chats.
- Pilot projects and A/B tests: Continuous experimentation with new approaches and measuring the effects in order to iteratively improve the strategy.
The organization of the future with regard to AI chat management must be agile, customer-oriented and data-driven. It is about creating a corporate culture that focuses on relevance, resonance and trust and consistently places the customer at the center. This is the only way for companies to master the challenges and successfully utilize the new possibilities of AI search.
Further questions or support required?
Do you have any questions? Are you unsure how to start reorganizing? Are you wondering where your organization stands today and how you can master the realignment?
I am happy to support you, act as a sparring partner and answer your questions. I am always happy to receive your messages, preferably by WhatsApp message or e-mail.
Even more input
In this report, you can find out how ChatGPT and co. have already changed the search behavior of your customers. The report examines various target groups based on age, sector, product, services and other characteristics.
And in the video interview with Sophie Hundertmark and Prof. Dr. Nils Hafner, the background and context of AI chat management are discussed in detail.
