{"id":8234,"date":"2026-04-30T14:04:18","date_gmt":"2026-04-30T12:04:18","guid":{"rendered":"https:\/\/nextra-consulting.com\/15-competitors-one-ai-agent-robust-results-rethinking-sustainability-benchmarking\/"},"modified":"2026-05-13T11:40:51","modified_gmt":"2026-05-13T09:40:51","slug":"praxisprojekt-ki-agent-im-einsatz-maritim","status":"publish","type":"post","link":"https:\/\/nextra-consulting.com\/en\/praxisprojekt-ki-agent-im-einsatz-maritim\/","title":{"rendered":"15 competitors, one AI agent, robust results: Rethinking sustainability benchmarking"},"content":{"rendered":"\t\t
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Anyone who wants to make strategic decisions on sustainability<\/strong> needs more than a gut feeling. They need orientation: What are others doing? Where do we stand ourselves? And what is really common practice in our industry? These were exactly the questions at the start of our joint project with Maritim Hotelgesellschaft<\/strong>. The goal was systematic sustainability benchmarking<\/strong> that not only captures what competitors communicate at a superficial level, but also provides a well-founded assessment of the industry and your own position\u2014and delivers concrete input for strategic work<\/strong>. <\/p>

The starting point: Rethinking benchmarking<\/strong><\/span><\/h6>

To gain an overview of sustainability performance in the industry, Maritim has conducted benchmarking analyses in the past. However, these were limited to a manageable number of competitors, topics, and sources\u2014a necessary limitation<\/strong> to keep the manual effort within reasonable bounds. <\/p>

In our discussions, the idea emerged to rebuild the process with AI support<\/strong>: Using an AI agent, the analysis would be automated<\/strong>, so that all competitors and criteria relevant to Maritim could become part of the benchmarking\u2014at a scale that would not be realistic with manual work.<\/p>

The project kicked off with a classic benchmarking approach<\/strong>: Together, we defined the \u201crelevant set\u201d of 15 competitors and the analysis criteria. A careful selection process was particularly important, as the hotel industry\u2019s structure\u2014with different brands and corporate umbrellas\u2014does not automatically allow for robust comparability. The criteria to be examined as part of the benchmarking were mapped precisely to Maritim\u2019s ESG strategy<\/strong> to ensure maximum value. <\/p>

The methodological core: An AI agent<\/strong><\/span><\/h6>

For the actual analysis, we developed a benchmarking agent on an automation platform<\/strong>. The agent first systematically researched publicly available information, such as company websites, sustainability reports, press releases, and other sources. This content was fed into a vector database<\/strong>, which the agent used to run through the defined criteria for each of the 15 companies, extract relevant information, and output the results in a structured, tabular format. The result was a consistent, comparable data set<\/strong> across all competitors\u2014created significantly faster than purely manual research would have allowed. <\/p>

More room for what really matters<\/strong><\/span><\/h6>

A key value of the project was the time saved<\/strong>, as the extensive research across numerous competitors and sources could be significantly accelerated. Henning J\u00fcnke, Director of Sustainability at Maritim Hotelgesellschaft mbH, confirms: \u201cBoth the breadth and the depth of the results increased significantly. With AI, far more was possible than before.\u201d<\/strong> Even more important, however, was what the time savings made possible: more room for the actual strategic work<\/strong>. The newly freed-up capacity could be used to interpret the results, derive best practices, and assess their relevance for Maritim. This shift from manual data collection to well-founded interpretation<\/strong> was one of the project\u2019s key successes. <\/p>

From the outset, one thing was clear: AI-supported results must not be adopted uncritically. The human-in-the-loop approach<\/strong> was therefore a core principle. The AI handled the structured analysis of large volumes of information; expert review and quality assurance remained with people with sustainability expertise. This is the prerequisite for results that are not only available quickly, but also strategically usable. <\/p>

Concrete insights for strategic decisions<\/strong><\/span><\/h6>

The value became especially tangible in specific questions.<\/strong> One example: Should CO\u2082 emissions from guests traveling from overseas, for instance, be part of your own corporate carbon footprint? The analysis showed that this is not common practice in the hotel industry so far. This clear classification provided additional strategic confidence in the decision to keep the boundary comparable. <\/p>

In addition, the benchmarking made it visible which sustainability approaches other companies are already pursuing<\/strong> and where new impulses for your own further development can be derived. For Maritim, this created not only a one-time baseline assessment<\/strong>, but also a foundation on which progress can be measured in the future\u2014for example through an annual update. Thanks to the AI agent used, such regular analysis is possible with minimal effort. Henning J\u00fcnke emphasizes: \u201cWith the AI benchmarking, which we want to repeat regularly in the future, we now have a solid basis for measuring our progress.<\/strong> This allows me, for example, to show internally where we started on sustainability and where we stand today<\/strong>.\u201d <\/p>

Transferable far beyond the hotel industry<\/strong><\/span><\/h6>

The approach developed is not industry-specific.<\/strong> The methodological framework can be used effectively wherever large volumes of documents, reports, or web pages need to be systematically evaluated<\/strong>\u2014whether for sustainability benchmarking, analyzing regulatory requirements, or preparing extensive reporting landscapes. Criteria and focus areas can be adapted depending on the context. <\/p>

The project with Maritim shows that AI creates value in sustainability management especially when it is used purposefully:<\/strong> as a tool for the structured analysis of large volumes of information and as a lever for greater efficiency and market transparency. The expert perspective remains indispensable<\/strong>. Henning J\u00fcnke confirms: \u201cSimply using AI would not have created much added value for us. But the combination of AI and Nextra\u2019s sustainability expertise really impressed me.<\/strong>\u201d Because it is only this interplay of technological support and human evaluation that turns data into strategically usable insights. <\/p>

You can find the full Sustainability x AI Talk on the project here:<\/strong><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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If you are dealing with similar questions in your company and are interested in a structured market or competitive assessment, feel free to get in touch.<\/p>

You can find our services around sustainability strategy here<\/a><\/span><\/span>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Anyone who wants to make strategic decisions on sustainability needs more than a gut feeling. They need orientation: What are others doing? Where do we stand ourselves? And what is really common practice in our industry? These were exactly the questions at the start of our joint project with Maritim Hotelgesellschaft. The goal was systematic […]<\/p>\n","protected":false},"author":8,"featured_media":7673,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[66,86],"tags":[],"class_list":["post-8234","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai","category-ai-agents"],"_links":{"self":[{"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/posts\/8234","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/comments?post=8234"}],"version-history":[{"count":3,"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/posts\/8234\/revisions"}],"predecessor-version":[{"id":8798,"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/posts\/8234\/revisions\/8798"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/media\/7673"}],"wp:attachment":[{"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/media?parent=8234"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/categories?post=8234"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/nextra-consulting.com\/en\/wp-json\/wp\/v2\/tags?post=8234"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}