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Our Team

Laura Colm (Bocconi University, Milan)

Torsten Bornemann (Goethe University, Frankfurt)

Jessica Hoppner (GMU, Fairfax)

Andrea Ordanini (Bocconi University, Milan)

EMAC 2025 - B2B Connect Research Symposium

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The Industry View: AI Big Promises (and challenges) for B2B Sellers

A lot of B2B sellers seem to have embraced the use of AI
AI seems to be used across several B2B sales touchpoints
Some expected benefits of AI seem uncertain for B2B sellers

EMAC 2025 - B2B Connect Research Symposium

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The Industry View: AI Big Promises (and challenges) for B2B Buyers

A lot of B2B buyers seem to have embraced the use of AI too
AI seems to be used also across several B2B purchase touchpoints
Some expected benefits of AI seem hard to achieve for B2B buyers too

EMAC 2025 - B2B Connect Research Symposium

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The Academic View: A Scattered Picture of AI for B2B Exchanges

Mktg is paying more attention to study AI in B2C vs. B2B contexts

15 out of the 21 (71%) empirical studies with the word AI in the title & published in the top5 Mktg journals focus on final consumers

The very few B2B studies on AI in Mktg top journals suggest contingent effects of AI

e.g., in sales, Habel et al. (forthcoming) show AI for leads nurturing is favorable especially for new (vs. old) contacts

Overall, B2B Mktg studies on AI prioritize the seller (vs. the buyer) perspective

🡪 Empirical studies with the words AI & sales in the title are 38 in the EBSCO database, while those with the words AI & procurement in the title are just 11

EMAC 2025 - B2B Connect Research Symposium

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Our research

Industry seem to portray two different pictures of AI diffusion in B2B

RQ₁ 🡪 What is the ‘real’ perimeter of the use of AI (vs. human) in B2B exchanges?

Industry and Academia seem to suggest heterogeneity in the exploitation of AI potential in B2B

RQ₂ 🡪 What are customers’ benefits/drawbacks from using AI (vs. human) in B2B exchanges?

Method

We adopt a Value-In-Use viewpoint (Macdonald et al. 2016) and take the customer (vs. seller) perspective in studying AI on B2B exchanges

We take a Theory-In-Use empirical approach (Zeithaml et al. 2020) to generate grounded, practitioner-informed knowledge on B2B uses of AI

🡪 So far, 5 in-depth interviews with “relevant” B2B players, e.g., industry associations key members, organizational buyers from different industries, AI business consultants, … (more to come)

Large-scale field studies will then attempt to validate/extend the grounded-theory evidence

EMAC 2025 - B2B Connect Research Symposium

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Discussion pitches (for you to help us …)

Industry reports and anecdotal evidence seem to suggest a widespread adoption of AI tools to assist B2B exchanges. Yet, our preliminary evidence consistently points out that both sellers and buyers seem to be prudent in adopting AI solutions in the B2B context.

What is your view and experience about this apparent volume mismatch?

EMAC 2025 - B2B Connect Research Symposium

There is a general reluctance in adopting AI B2B solutions, more in the case of buyers

Regarding AI, I haven't seen it yet. It's definitely the hot buzzword. And I know we're looking internally on the buyer side, with ways to best utilize it. But it's really in the exploratory phase at this point.

Well, you know, there's a lot of talk about it out there, of course. We haven't seen a lot of it enter our industry yet.

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Discussion pitches (for you to help us …)

Our preliminary evidence indicates that AI is currently more beneficial in operative tasks such as preparation of complete offers/requests or document checking, but less useful in searching tasks such as lead generation/supplier scouting (low scale problem) and personalization (message templatization)

What is your view and experience about this apparent content mismatch?
What is your view about the more and less promising areas for AI use in B2B exchanges?

EMAC 2025 - B2B Connect Research Symposium

AI is less used for relationships and more for database inquiry and accuracy of quotes. There is fewer use for message crafting, but its utility is not so high: AI messages are often templatized

AI is mostly used for contract completeness. Just to have faster reviews on the terms and conditions and the clauses and like the delivery dates, and all of that. Much less for negotiation

AI is also used for document recognition.

And then just automatically determining the content, based on some keywords, - is it part of the business that they want to compete in and then linking it to some sort of a statement of work.

AI value-added is on efficiency/speed and sharing the knowledge in the organization, not in doing something novel or creative

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Discussion pitches (for you to help us …)

Our preliminary evidence suggests the ‘human touch’ remains important in AI-assisted B2B exchanges for: i) relationship trust; ii) adaptation in the implementation; iii) data security and privacy

What is your view and experience about these roles expected for humans into an AI-augmented B2B exchange environment?

EMAC 2025 - B2B Connect Research Symposium

But if you have the assist from the AI technology, you know, I think that still takes a human element to build relationships.

Yes, there's always the concern that just from a relationship standpoint. It's always nice to talk to a human, because you can always get to the right information.

The other question, I guess, comes around against data, and how you're leveraging that. The key question mark is data privacy.

The effective use of AI depends on its level of integration in the organization system (through APIs) and the HR skills. These are key at the moment.

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