GSThe Goldman Sachs Group, Inc.
AI adoption · Q1 2026 earnings call
FinancialsPiloting
7
extracted from this call
3 / 5
operational, no hard numbers
Not disclosed
no breakout in this call
AI was discussed on this call in four distinct contexts: (1) as a macro force driving market volatility and sector disruption (software), (2) as a cybersecurity risk vector tied to advancing LLM capabilities, (3) as an internal productivity and efficiency driver under the 'One Goldman Sachs 3.0' initiative with foundational cloud/data investments underway, and (4) as a long-term enterprise growth accelerant that management views as highly constructive for Goldman's franchise. Management was directional but not quantitative on internal AI deployment, and no AI revenue attribution was disclosed.
Hybrid
See full leaderboard →27/ 100
51
stage: piloting · max spec: 3
0
no quantified disclosure
35
1 scope
internal_use
7 AI mentions from this call.
Extracted verbatim from the GS Q1 2026 earnings call transcript. Speaker, section, and specificity tier surfaced for each mention.
- T3Q&A· CEO· Internal useBanks EUs were in D.C. on Friday around concerns around some of the AI-driven risks to banking infrastructure. Anything you can share with us in terms of like is this something extremely different than what banks have had to deal with over the last decade.
“Obviously, the LLM are making rapid progress, and we're hyper-aware of the enhanced capabilities of these new models. With the help of the U.S. government and the model publishers, we are very focused on supplementing our cyber and infrastructure resilience and this is part of our ongoing capabilities that we have been investing in and are accelerating our investment in. We're aware of [indiscernible] and its capabilities. We have the model. We're working closely with Anthropic and all of our security vendors to kind of harness frontier capabilities wherever it's possible, and this will continue to be an important focus”
— David Solomon, GS earnings callAnthropic, U.S. government - T3Prepared remarks· CFO· Internal use
“we are thoughtfully building out our One Goldman Sachs 3.0 work streams, and our early learnings have reinforced the need to double down on the foundational elements of our infrastructure. We are, therefore, accelerating our investments in cloud migration, and in the accuracy, completeness and timeliness of our data. These investments are critical to optimizing the deployment of AI solutions across the firm, which will allow us to unlock greater productivity and efficiency opportunities over time.”
— Denis Coleman, GS earnings callOne Goldman Sachs 3.0 - T3Prepared remarks· CEO· Internal use
“clients seek our views and analysis around a range of topics, including AI, and we were able to speak to these trends from firsthand experience as we thoughtfully implemented new technologies across our 6 initial work streams and around the firm more broadly. We remain confident that over time, One GS 3.0 will drive stronger operating leverage, greater resilience and improved efficiency and returns and allow us to continually elevate service to our clients.”
— David Solomon, GS earnings callOne GS 3.0 - T2Q&A· CEO· Customer demand signalJust another question on artificial intelligence. Obviously, I think investors are going business by business, just trying to understand implications. And so good just to hear how you're thinking about what businesses will be most impacted and just whether AI overall is an accelerant for Goldman Sachs like it has been -- or technology cycles in the past have been?
“I am hugely forward leaning on the power of this technology to accelerate growth and efficiency in Goldman Sachs allow us to more aggressively invest in growth in areas of our business where, for a variety of reasons, over the course of the last 5 years, we've been more constrained than I think we're going to be for the next 5 years. I think this is true not only with Goldman Sachs, I think this is true with lots of other businesses with enterprises broadly, and as enterprises take advantage of that, that spurs activity that feeds in the Goldman Sachs ecosystem. So I do think as in other technology supercycle, this is extraordinarily constructive for Goldman Sachs.”
— David Solomon, GS earnings call - T2Prepared remarks· CEO· Customer demand signal
“the macro environment started to weigh on sentiment, volatility increased meaningfully with concerns around AI-driven disruption, sectors like software, heightened uncertainty in parts of private credit and the conflict in the Middle East.”
— David Solomon, GS earnings call - T2Q&A· CFO· Internal useYou'd indicated some front-loading of infrastructure investments, cloud migration in advance of AI-driven investments that you plan on making? Just given all the investments that you cited in terms of what you're deploying on the platform. How should we think about the trajectory of non-comms.
“the more we focus and do work on it, we appreciate that having greater capacity to migrate activities to the cloud and to harness a lot of value from data sense orders for investment now to drive unlock in future periods.”
— Denis Coleman, GS earnings call - T1Prepared remarks· CEO· Customer demand signal
“The combined effects of fiscal stimulus and developed economies, ongoing AI-related capital investment and a more balanced regulatory agenda in the U.S. are powerful forces.”
— David Solomon, GS earnings call
What management wouldn’t quantify.
Analyst questions where management declined to share a specific number. The pattern of refusals is often as informative as the disclosures.
- No quantification of AI-related cost savings, productivity gains, or headcount impact from One GS 3.0 work streams despite direct analyst question on efficiency trajectory (Wolfe Research / Steven Chubak).
- No disclosure of specific AI tools, models, or vendors deployed internally beyond a passing reference to Anthropic for cybersecurity purposes.
- No AI revenue attribution or bookings figure provided; management did not address whether AI-related client advisory or capital markets activity is tracked separately.
- Analyst Devin Ryan (Citizens) asked a broad AI question; management responded with qualitative optimism but declined to provide any metrics on internal deployment progress, adoption rates, or timeline to efficiency realization.
- CFO referenced 'accelerating investments in cloud migration and data accuracy' as prerequisites for AI deployment but gave no capex or opex figure associated with these investments.
- No disclosure on number of employees using AI tools, number of active work streams beyond '6 initial,' or any leading productivity metric.
Compare with peers.
Other companies in the same sector and at the same AI adoption stage.
Same GICS sector, all stages
Independent research, direct to your inbox.
Live data tracking and analysis. Deep research that cuts through consensus. Evidence-backed insights.