Description
In this episode of Thoma Bravo’s Behind the Deal, Managing Partner Holden Spaht sits down with Charles Gottdiener, CEO of Anaplan, and Leagh Turner, CEO of Coupa, to discuss how enterprise software leaders are turning AI innovation into real business impact.
Drawing on their experience as both builders and users of AI, they share how AI is driving productivity, reshaping operating models, and expanding operating leverage—while highlighting the importance of governance, disciplined pricing, and domain expertise as AI adoption accelerates.
For more information on Thoma Bravo's Behind the Deal, visit https://www.thomabravo.com/behindthedeal
Learn more about Thoma Bravo: https://www.thomabravo.com/
Learn more about Anaplan: https://www.anaplan.com/
Learn more about Coupa: https://www.coupa.com/
Disclaimer: This podcast is for informational purposes only and does not constitute an advertisement. Views expressed are those of the individuals and not necessarily the views of Thoma Bravo or its affiliates. Thoma Bravo funds generally hold interest in the companies discussed. This podcast should not be construed as an offer to solicit the purchase of any interest in any Thoma Bravo fund.
Certain statements about Thoma Bravo made by portfolio company executives are intended to illustrate Thoma Bravo's business relationship with such persons rather than Thoma Bravo's capabilities or expertise with respect to investment advisory services. Portfolio company executives were not compensated in connection with their podcast participation, although they generally received compensation and investment opportunities in connection with their portfolio company roles and in certain cases are also owners of portfolio company securities and or investors in Thoma Bravo funds. Such compensation and investments subject podcast participants to potential conflicts of interest. In addition, this podcast includes forward-looking statements. These statements are based on current expectations and assumptions and involve significant risks and uncertainties that could cause actual results to differ materially.