← back to rankingTTWO · Take-Two Interactive Software, Inc.
Electronic Gaming & Multimedia · mkt cap $41.3B · calls: Q4 FY2026 vs Q3 FY2026
37.0 conviction · conf-adj 37
conf 6/10 partial
enthusiasm:27.0 · trend:8 · quantifies:5 · impact:0 · under_radar:0 · credibility:0 · business_impact:4 · disruption:-6 · commitment:-4 · confirmation:3
Enthusiasm latest 9 / prev 8 (rising)
Take-Two’s AI thesis is mainly bottom-line: AI and predictive models should improve asset creation, ad production, user acquisition, development workflows, and margins, while management rejects the idea that AI alone creates hit games. The latest call is more credible than the prior one because it adds a concrete cost-saving example and ties AI explicitly to margin improvement, though revenue upside remains unquantified. Management is enthusiastic but disciplined, repeatedly emphasizing human-led creative control and AI as an efficiency/innovation tool rather than a replacement for game development.
GROUNDED NEXT-FY IMPACT vs CONSENSUS
Grounded on actual base — revenue $6.7B · net income $-0.3B · net margin -4.5% · diluted EPS -1.62
These are next-fiscal-year annual uplift estimates, not next-quarter numbers.
Aggregate next-FY est. rev uplift: 0.0% · next-FY EPS uplift: % · vs analysts: inline · priced in: high · confidence: 6/10
| Claim | Figure | Arithmetic | Next-FY Rev % | Next-FY EPS % |
|---|
AI-created ad spot production cost avoided
cost | $0 vs $25,000–$100,000 per spot previously (one two-person studio) | Disclosed saving up to $100,000 per ad spot; after-tax @21% = $100,000×0.79 = $79,000 (range $19,750–$79,000). Cost saving, so topline lift = 0% ($100,000/$6,656.4M ≈ 0.0015% even as a cost item — immaterial). EPS-uplift undefined: company is loss-making (NI = −$298.2M), so dividing a positive saving by a negative base is meaningless → null per guardrail. | 0 | |
Marketing team tied to AI use case is two people
other · soft | 2 people | Descriptive headcount only — no prior team size, salary base, companywide FTE reduction, or dollar saving disclosed or derivable. No base obtainable → unanchored. | | |
Hundreds of generative-AI pilots and implementations companywide
productivity · soft | 'hundreds' of pilots, 'efficiencies', 'reduce costs' | No dollar figure, no % productivity, no headcount, no affected revenue line. Qualitative only — nothing to anchor arithmetic to → soft. | | |
Assumptions: Tax rate 21%. Cost savings treated as bottom-line only (no incremental capacity/volume claimed) → topline ~0. The only disclosed dollar figure is a per-spot ad-production saving of up to $100,000 at a single two-person studio — anecdotal, not a companywide run-rate; no annual spot volume disclosed, so it cannot be scaled. Company is loss-making (NI = −$298.2M, net margin −4.48%), so EPS-uplift % is mathematically meaningless and nulled per guardrail. All claims are adopter-side (AI improving TTWO's own marketing/production costs); no supplier-side AI revenue exists. Forward statements ('enhance our margin profile over time') are aspirational/unquantified → not sized.
Top line: Effectively none. The only quantified AI item is a per-spot cost saving, not a revenue source; no AI bookings, engagement, or take-rate figure was given. Aggregate adopter revenue uplift = $0 / $6.656B = 0.0%.
Bottom line: Immaterial and unmeasurable as EPS. The single hard figure — up to $100,000 saved per AI-made ad spot (~$79k after tax, range $19.75k–$79k) at one two-person studio — has no disclosed annual volume to scale, is ~0.0015% of revenue, and rounds to nothing against a $298.2M net loss; dividing it by the negative earnings base yields no meaningful EPS-uplift % (nulled). 'Hundreds of pilots' and the two-person team are qualitative color. Real margin help from AI, if any, is a multi-year aspiration framed 'over time,' with no quantum attached.
[EPS uplift n/m (loss-making base)] Consensus already projects a sharp swing driven by the product cycle (GTA VI), not AI: revenue $6,687.5M (FY26) → $8,574.4M (FY27, +28%) and EPS from −$1.62 to positive $6.75. The sizeable AI figure on the table (~$79k after-tax saving) is orders of magnitude below the noise floor of those estimates (~$1,124.3M FY27 net income). No quantified AI uplift points above consensus, so whatever efficiency materializes is comfortably absorbed within existing margin assumptions; nothing here is the under-priced case.
MODEL CONSENSUS (impact)
partial
Both agree: loss-making, EPS null, all adopter-side, only one hard but immaterial per-spot cost saving; no AI revenue driver.
Conflicts reconciled
- rev_uplift_pct/est_rev_uplift_pct: X=0 vs Y=0.0012 -> used 0 because it is a cost saving with topline ~0 per method
- supplier_rev_uplift_pct: X=0 vs Y=null -> used null because no supplier-side claim exists
- vs_analyst_expectations: X=unclear vs Y=inline -> used inline, better justified (AI saving below estimate noise floor)
- priced_in: X=medium vs Y=high -> used high, better justified and more conservative
- confidence: X=5 vs Y=7 -> used 6, lowered after resolving verdict conflicts
| Field | Opus 4.8 | GPT-5.5 |
|---|
| Rev uplift % | 0.0012 | 0 |
| EPS uplift % | – | – |
| Priced in | high | medium |
| vs analysts | inline | unclear |
| Confidence | 7 | 5 |
| Top line | Effectively none. The only quantified AI item is a cost saving, not a revenue source; no AI bookings, engagement, or take-rate figure was given. The $100k-per-spot marketing saving has zero topline effect and is 0.0012% of $6,656.4M revenue even as a cost item. AI is not a stated revenue driver. | No quantified AI revenue claim was disclosed. The only hard claim is a cost saving per ad spot, so aggregate adopter revenue uplift is $0 / $6.656B = 0.0%. |
| Bottom line | Immaterial and unmeasurable as EPS. The single hard figure — up to $100,000 saved per AI-made ad spot (~$79k after tax) at one two-person studio — is ~0.0012% of revenue and rounds to nothing against a $298.2M net loss; dividing it by the negative earnings base yields no meaningful EPS-uplift % (nulled). 'Hundreds of pilots' and the two-person team are qualitative color, not sizeable savings. Real margin help from AI, if any, is a multi-year aspiration management explicitly framed as 'over time,' with no quantum attached. | The hard, anchored saving is $19,750-$79,000 after tax per AI-created ad spot. Without spot volume, this cannot be scaled to companywide EPS, and current net income is negative, making EPS-uplift % not meaningful. |
| Reasoning | Consensus already projects a sharp swing driven by the product cycle (GTA VI), not AI: revenue $6,687.5M (FY26) → $8,574.4M (FY27, +28%) and EPS from positive $3.91 → $6.75 (+73%), turning from the current −$1.62 loss. The sizeable AI figure on the table (~$79k after-tax saving) is ~0.000026% of FY27 consensus net income (~$1,124.3M) — orders of magnitude below the noise floor of those estimates. There is no quantified AI uplift that points above consensus, so whatever efficiency materializes is comfortably absorbed within existing margin assumptions; nothing here is the 'interesting' under-priced case. | Consensus revenue rises from $6.688B for FY2026 to $8.574B for FY2027, a $1.887B increase or 28.2%. The disclosed hard AI math contributes 0.0% revenue uplift and only $19.75K-$79.0K after-tax saving per spot, with no disclosed annual volume. There is no evidence from the quantified claims that AI adds above the consensus trajectory. |
Rows highlighted where the two models disagreed.
QUANTIFICATIONS
AI-created ad production cost: $0 versus $25,000, $50,000, $100,000 previously (Q4 FY2026 real-world studio example, bottomline)
“The entire cost of making this spot was 0. And previously, we hired third-party companies to actually create those with human beings, and those spots could cost $25,000, $50,000, $100,000.”
Marketing team headcount tied to AI use case: two people (Q4 FY2026 real-world studio example, bottomline)
“The entire marketing team at this particular studio is two people.”
Generative AI pilots and implementations: hundreds (Q3 FY2026 current companywide activity, bottomline)
“We have hundreds of pilots and implementations across our company, including with our studios, and we are seeing opportunities to drive efficiencies, reduce costs, and create the opportunity to do what digital technology has always allowed, which is the mundane tasks become easier and less relevant, which frees up our creators to do the more interesting tasks of making superb entertainment.”
PAST (realized)
- The entire cost of making this spot was 0. And previously, we hired third-party companies to actually create those with human beings, and those spots could cost $25,000, $50,000, $100,000.
- But what AI has allowed them to do is be more efficient, make great stuff and do it cheaper. And this is all a benefit to our company.
- As it happens now, we're actively embracing generative AI. We have hundreds of pilots and implementations across our company, including with our studios, and we are seeing opportunities to drive efficiencies, reduce costs, and create the opportunity to do what digital technology has always allowed, which is the mundane tasks become easier and less relevant, which frees up our creators to do the more interesting tasks of making superb entertainment.
CURRENT (now)
- So we are constantly on a daily basis, tuning up our models that will inform how we spend money on user acquisition.
- We work with AppLovin, and we are trying to optimize, of course, our return on ad spend.
- I think that everyone has bought into the possibilities of new technology.
- To the extent that technology allows anyone to do a better job in asset creation, naturally, we'll avail ourselves with the same technology.
FORWARD (guidance)
- So as we operate at this new level and generate operational efficiencies through reduction efforts and leveraging new technologies, including AI, we aim to enhance our margin profile over time.
- As we continue to explore and invest in new technologies, particularly AI, we'll unlock greater efficiencies that will allow our talent to focus on the kind of innovation that has enabled us continually to set new creative and commercial benchmarks in interactive entertainment.
- I'm hopeful that it will also move into the category of creativity as it allows our creators to use digital tools to expand what we do to make it even more beautiful, engaging, and exciting.
- And if this tool bears out, it will make a component of what we do all that much better and more efficient.
TRACK RECORD — PROMISE vs DELIVERY
—/100 (no quantified promises) no-quantified-promises 6 calls reviewed
Across all six calls, Take-Two discussed AI, machine learning, personalization, telemetry, and technology-enabled efficiency only qualitatively or as current operating practice — e.g. Strauss citing 'hundreds of pilots' in generative AI and generic pledges to invest in AI for efficiencies. Management never paired a number with a timeframe or milestone, so there is no quantified AI promise to score and no delivery track record.
PRICED-IN (REFINED)
HIGH (already in)Est. revisions rising · Fwd P/E 88.6 · EV/Sales 6.4x
AI claim maps to Console, Mobile, P C And Other Products
Analyst ratings show mild upward migration recently, with holds falling to zero and buys rising, while forward revenue and EPS estimates embed strong growth through FY2027. Price targets are not accelerating, but they remain clustered well above the current price and consensus is already baking in a major earnings ramp. With a roughly 88.6x forward P/E and 6.4x EV/sales despite negative TTM earnings, the valuation is rich, so rising estimates make the AI upside more priced-in rather than less. AI-driven development efficiency or monetization upside would most plausibly flow through Console, Mobile, and P C And Other Products, supporting a high priced-in verdict.
COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS
2Q3 FY20254Q4 FY20254Q1 FY20264Q2 FY20265Q3 FY20265Q4 FY2026
AI enthusiasm across 6 calls — trend ↗ rising
AI-related story moved from minimal personalization mentions to explicit AI/technology investment for efficiency, creative capability, conversion, and margins.
RECENT AI CATALYSTS & NEWS
BUSINESS IMPACT - QUALITATIVE MATERIALITY
6/10 qualitative impact moderate medium-term · mixed evidence
Where AI matters: studio workflows, asset creation, marketing production, mobile user acquisition
AI is already being used for ad creation, user-acquisition optimization, and studio productivity, and those are real cost/margin levers for a content-heavy game publisher. But the hard evidence is still small relative to Take-Two's scale, and management explicitly frames AI as helping efficiency and innovation rather than replacing the core work of making hit games.
Caveats: AI savings may remain fragmented and immaterial versus AAA development and marketing budgets; Lower-cost AI-generated games could intensify competition for player time, especially in mobile; Legal, labor, IP, and platform policy constraints may slow use of generative AI in shipped products; Management enthusiasm is high but revenue or EPS contribution is largely unquantified
AI DISRUPTION / CANNIBALIZATION RISK two-sided · 4/10
AI could lower barriers for asset creation and small-game production, increasing content supply and pressure in lower-end/mobile markets. The core model is still relatively durable because Take-Two monetizes scarce franchises, production quality, IP, distribution, and live-service communities rather than generic content alone.
OPTIONS / MARKET STRUCTURE
option liquidity: good
proxy inputs — dollar-ADV $454M · beta 0.973 · px $222.38
source: proxy (no options chain on FMP)
FMP /stable/ exposes no options-chain endpoint on this key, so ATM IV, bid-ask spread and open interest are unavailable. Liquidity below is a PROXY from dollar-ADV, beta and price level (a stand-in for option depth), not measured option-market data.
CONFIRMATION — INSIDERS · 13F · LANGUAGE
Mixed — insiders selling, institutions adding, management language 2/10 hedged.
INSIDERS selling 34 open-market sell(s) vs 0 buy(s) — net distribution
INSTITUTIONS (13F) adding as of 2026-03-31: 150 new / 189 closed positions; 565 increased / 337 reduced; institutional ownership -3.52pp; -41 net 13F holders
MGMT LANGUAGE 2/10 hedged AI is barely discussed; technology/efficiency language is broad, aspirational, and lacks AI-specific ownership, timelines, or quantified impact.
commit “which is generating improvements in conversion and customer loyalty.”
hedge “we believe that we're extraordinarily well positioned to take measured creative risks”
hedge “to invest in technology that will unlock greater creative capabilities and operational efficiencies across our organization.”
VERBATIM AI QUOTES
“We remain enormously optimistic.”
— Strauss Zelnick, Q4 FY2026
“To the extent that technology allows anyone to do a better job in asset creation, naturally, we'll avail ourselves with the same technology.”
— Strauss Zelnick, Q4 FY2026
“I hope that's true because that will benefit us naturally. We have a 3-part strategy, be the most creative, be the most innovative, be the most efficient. It seems to me that even if it doesn't help with creativity, it certainly should help with efficiency and innovation.”
— Strauss Zelnick, Q4 FY2026
“The entire cost of making this spot was 0. And previously, we hired third-party companies to actually create those with human beings, and those spots could cost $25,000, $50,000, $100,000.”
— Strauss Zelnick, Q4 FY2026
“But what AI has allowed them to do is be more efficient, make great stuff and do it cheaper. And this is all a benefit to our company.”
— Strauss Zelnick, Q4 FY2026
“So as we operate at this new level and generate operational efficiencies through reduction efforts and leveraging new technologies, including AI, we aim to enhance our margin profile over time.”
— Lainie Goldstein, Q4 FY2026
“So we are constantly on a daily basis, tuning up our models that will inform how we spend money on user acquisition.”
— Strauss Zelnick, Q4 FY2026
“I think that everyone has bought into the possibilities of new technology.”
— Strauss Zelnick, Q4 FY2026
“You have to assume that they're going to be the first people to embrace new technology that allows them to do a better job.”
— Strauss Zelnick, Q4 FY2026
“Our art is created by human beings using computers, and I believe that will continue to be the case.”
— Strauss Zelnick, Q4 FY2026
“As we continue to explore and invest in new technologies, particularly AI, we'll unlock greater efficiencies that will allow our talent to focus on the kind of innovation that has enabled us continually to set new creative and commercial benchmarks in interactive entertainment.”
— Strauss Zelnick, Q3 FY2026
“As it happens now, we're actively embracing generative AI. We have hundreds of pilots and implementations across our company, including with our studios, and we are seeing opportunities to drive efficiencies, reduce costs, and create the opportunity to do what digital technology has always allowed, which is the mundane tasks become easier and less relevant, which frees up our creators to do the more interesting tasks of making superb entertainment.”
— Strauss Zelnick, Q3 FY2026
“And generative AI squarely falls within the category of innovation and is already moving into the category of efficiency.”
— Strauss Zelnick, Q3 FY2026
“I'm hopeful that it will also move into the category of creativity as it allows our creators to use digital tools to expand what we do to make it even more beautiful, engaging, and exciting.”
— Strauss Zelnick, Q3 FY2026
“It certainly doesn't replace the creative process.”
— Karl Slatoff, Q3 FY2026
“So that's just a very, very small component of what we do. And if this tool bears out, it will make a component of what we do all that much better and more efficient.”
— Karl Slatoff, Q3 FY2026
ANALYST QUESTIONS ON AI
Q (Q4 FY2026, Cory Carpenter): And maybe as a follow-up, Strauss, on the last earnings call, Google Genie had just launched in beta. There's been some conversations more recently around the ability for AI to perhaps create GTA VI in a couple of months. I know this is a bit of a generic high-level question you've touched on before, but just given this remains a pretty big debate among investors, I thought it would be helpful to hear your latest views just around what you're seeing in AI and how you expect it to change the gaming industry in Take-Two in particular.
A: We remain enormously optimistic. Technology helped build this company. Video games are created largely inside computers and always have been. I think the sort of confusion surrounds a belief that somehow more efficient asset creation puts us at some disadvantage or creates a competitive advantage for someone else. And I just don't believe that's the case.
Q (Q4 FY2026, Eric Sheridan): With respect to mobile advertising and building additional optimization around user acquisition, how are you thinking about the signals as more mobile advertising becomes driven by AI and machine learning with respect to either being able to deploy more dollars at a higher return on ad spend or possibly becoming more efficient with respect to advertising?
A: We work with AppLovin, and we are trying to optimize, of course, our return on ad spend. So we are constantly on a daily basis, tuning up our models that will inform how we spend money on user acquisition. To answer your question, are there new opportunities to be more efficient in this area? Yes, I believe so.
Q (Q4 FY2026, Michael Hickey): Do you feel like at this point, you've got broad buy-in from your studio leadership around the use of AI tools, not just in marketing, but in game development. And when you think about these tools over time, I know you're doing a lot in terms of investing in product tools related to AI. Do you think this will allow you and your studio teams to unlock maybe some dormant franchise IP or even new IP that may not have been produced over the last decade plus due to resource constraints? And if that's the case, would you look to build headcount into that opportunity?
A: I think that everyone has bought into the possibilities of new technology. You have to assume that they're going to be the first people to embrace new technology that allows them to do a better job. That said, we're known for making these beautiful handcrafted titles around here.
Q (Q3 FY2026, Doug Creutz): The last few days, the equity markets have really punished your stock and those of other video game makers because of fears about what AI means for your business. I wondered, Strauss, if you'd like to expound upon whether you think what's happening in the market is an accurate reflection of the threats and opportunities you see coming from AI.
A: As it happens now, we're actively embracing generative AI. We have hundreds of pilots and implementations across our company, including with our studios, and we are seeing opportunities to drive efficiencies, reduce costs, and create the opportunity to do what digital technology has always allowed, which is the mundane tasks become easier and less relevant, which frees up our creators to do the more interesting tasks of making superb entertainment.
Q (Q3 FY2026, Andrew Marok): Maybe specifically, again, back to the commentary on generative AI. You know, we hear loud and clear Take-Two's ability to harness that. But maybe on Genie specifically, we've been getting a lot of questions from investors about the similarities and differences between world models and game engines. Can you maybe give us an overview of what you think tools like Genie can and cannot do as it relates to some of the proprietary game engines that you operate?
A: Genie is not a game engine, and I would it's very exciting technology, and I think the question is, how can it benefit our creators? It certainly doesn't replace the creative process. And if this tool bears out, it will make a component of what we do all that much better and more efficient.