← back to rankingIBM · International Business Machines Corporation
Information Technology Services · mkt cap $309.4B · calls: Q1 FY2026 vs Q4 FY2025
78.0 conviction · conf-adj 78
conf 6/10 partial
enthusiasm:30.0 · trend:8 · quantifies:12 · impact:4 · under_radar:0 · credibility:12 · business_impact:8 · disruption:-6 · commitment:6 · confirmation:4
Enthusiasm latest 10 / prev 9 (rising)
IBM's AI thesis is that enterprise AI pulls through its enabling software, data, automation, Red Hat, consulting, and Z infrastructure rather than depending on owning the application layer. Credibility improved in Q1 FY2026 because management moved from a broad GenAI book-of-business metric to more embedded revenue, backlog, productivity, and capacity metrics. The strongest evidence is quantified: AI software revenue north of $1.5 billion, consulting GenAI ARR above $4 billion, 30% consulting backlog penetration, 45% developer productivity gains, and $4.5 billion of productivity savings since 2023.
GROUNDED NEXT-FY IMPACT vs CONSENSUS
Grounded on actual base — revenue $67.5B · net income $10.6B · net margin 15.7% · diluted EPS 11.17
These are next-fiscal-year annual uplift estimates, not next-quarter numbers.
Aggregate next-FY est. rev uplift: 2.0% · next-FY EPS uplift: 8.0% · vs analysts: inline · priced in: high (model's call-read: medium; verdict above is the hard-data one used for ranking) · confidence: 6/10
| Claim | Figure | Arithmetic | Next-FY Rev % | Next-FY EPS % |
|---|
GenAI book of business $12.5B cumulative (sw $2B + consulting $10.5B)
revenue | over $12.5B inception-to-date | Cumulative BOOKINGS since 2023 (~3yr), NOT annual revenue. The recognized flow off this book shows up as the $4B consulting ARR + $1.5B software AI revenue rows below; counting the $12.5B (or its sub-books) as next-FY revenue would double-count and ignore ratable conversion. Not separately added. | | |
Consulting GenAI revenue/ARR: $3.6B (Q4'25 exit) -> $4B+ (Q1'26), >20% of consulting rev
revenue | $4B ARR; >20% of consulting revenue | Consulting ~$20B segment; GenAI >20% = ~$4B (consistent w/ ARR). GenAI is integrated across engagements (30% of backlog) and largely CANNIBALIZES traditional consulting, so the $4B is not all incremental. Net incremental = acceleration (~2.5pts on $20B = ~$500M) plus ARR step-up (~$0.7B/yr) -> assume ~$750M truly incremental next FY = 750M/67,535M = 1.11% of total rev; @20% incr consulting margin -> $150M / $10,593M NI = 1.4% EPS. | 1.11 | 1.42 |
Software AI platform $1.5B TTM, growing >40%, contributing 2pts software growth
revenue | north of $1.5B; >40% growth; 25% penetrated | $1.5B TTM x 40% growth = ~$600M incremental next FY = 600M/67,535M = 0.89% of total rev. Software AI is high-margin; @45% incremental margin -> $270M / $10,593M NI = 2.55% EPS. Mgmt: ~2pts of software growth annualized. (Y instead converted the $2B software book at 50% -> $1.0B/1.48%/2.83%; preferred X's organic-revenue anchor to avoid counting bookings as revenue.) | 0.89 | 2.55 |
Data revenue grew 19% (Q4'25) / 16% (Q1'26) on GenAI demand
engagement · soft | 19% / 16% growth | Sub-segment growth %, but Data dollar base not disclosed and Q1 figure is partly INORGANIC (Confluent, closed mid-March). Cannot size standalone without double-counting the software AI platform row that already captures GenAI product pull. Marked soft. (Both X and Y nulled this.) | | |
Consulting GenAI penetration: >15%->20% of rev, 30% of backlog ($32B), 40% of signings
engagement · soft | >20% rev / 30% backlog / 40% signings | Penetration ratios; the revenue they imply is already captured by the $4B ARR row. Backlog/signings momentum underpins low-mid single-digit consulting growth but adds no separable $ base. Not re-added (Y double-counted these as 2.96%/3.55% conversions on the $32B backlog; rejected as double-count of the ARR). | | |
AI productivity savings: $4.5B run-rate exiting 2025; +$1B in 2026
cost | $4.5B run-rate + $1B incremental 2026 | $4.5B is already in the EXIT run-rate -> embedded in the 2026 base (Y's 33.56% EPS from the full $4.5B is wrong: it double-counts the base). The NEW saving for next FY is the +$1B. After-tax @21% = $790M; /$10,593M NI = 7.46% EPS GROSS (both X and Y agree on the +$1B = 7.46%). Caveat: mgmt explicitly reinvests most savings (margin + hiring + R&D), so realized EPS accretion is materially below gross. Topline ~0. | | 7.46 |
Project Bob: 20k+ -> all developers, 45% productivity
productivity · soft | 45% gains; whole dev workforce | A component of the $4.5B/$1B savings program above; no separate developer payroll/cost base disclosed -> not added to avoid double-count. (Both X and Y left EPS uncomputable; topline 0.) | 0 | |
Mainframe AI: Z17 +50% inferencing, Spyre 450B inf/day @1ms, MIPS 3x, fraud saves 'tens of millions'
revenue · soft | qualitative (50%, 450B/day, 3x, tens of millions) | Selling AI inference capacity/silicon INTO clients = supplier-side; drives Z hardware & MIPS demand but AI-attributable $ revenue is NOT disclosed. The 'tens of millions' fraud saving is the CLIENT's P&L, not IBM's. Unquantified -> excluded from adopter headline. (Both X and Y nulled.) | | |
Assumptions: Earnings base: GAAP NI $10,593M / EPS $11.17 (consensus uses adjusted ~$10,733M/$11.36 — within 1.3%, no distortion, so EPS% sized off the GAAP base). Tax 21%. Incremental margins: software AI 45% (high-margin platform), consulting GenAI 20% (services). Phasing: the $12.5B GenAI book (sw $2B + consulting $10.5B) and the >20%/30%/40% penetration ratios are bookings/mix metrics — recognized ONLY via the disclosed ARR/run-rate flows ($4B consulting ARR, $1.5B software AI), NOT as separate lump conversions, to avoid double-counting. Consulting GenAI ARR treated as largely cannibalizing traditional consulting — only ~$750M of the $4B counted as net-incremental next FY. Savings: only the +$1B 2026 increment counted ($4.5B already in exit base) and haircut for reinvestment. Supplier-side mainframe AI excluded from headline (unquantified).
Top line: Adopter-side AI adds ~2.0% to total revenue next FY: ~0.89% from the software AI platform ($1.5B TTM x 40% = ~$600M incremental, the cleanest hard anchor and mgmt's stated '2 points of software growth'), plus ~1.1% from net-incremental consulting GenAI (~$750M, after stripping cannibalization out of the $4B ARR). The headline $12.5B GenAI book and >20%/30%/40% penetration metrics are bookings/mix ratios — they corroborate momentum but are not additive revenue (Answer Y's 5–6%+ topline came from converting these books AND the ARR, which double-counts). Mainframe AI (Z17/Spyre, 450B inf/day) is supplier-side and unquantified, so excluded.
Bottom line: Gross adopter EPS math sums to ~11.4%: revenue flow-through ~4.0pts (software ~2.55 + consulting ~1.42) plus the +$1B 2026 productivity increment at ~7.46pts after-tax. But IBM explicitly REINVESTS the bulk of its AI savings, so realized EPS accretion is well below the gross savings line — haircut to a realistic ~8% combined (revenue ~4 + a partially-banked savings contribution ~4). Thin-margin artifact is not a concern (15.7% net margin). Answer Y's ~33%+ EPS from booking the full $4.5B run-rate is rejected: that base is already embedded in 2026 earnings.
Consensus already embeds the AI story: 2026 revenue $71.47B = +5.8% vs 2025, and 2026 EPS $12.44 = +9.4% vs the $11.36 base. My adopter AI uplift (~2.0% rev, ~8% EPS) sits inside those consensus deltas — i.e., the analysts have substantially priced the GenAI acceleration and the productivity program. The case for modest upside (why 'medium' not 'high'): consulting GenAI ARR stepped from $3.6B (Q4'25) to $4B+ in a single quarter, backlog penetration rose 25%->30% in one quarter, and mgmt's 'can we do better than low-single-digit consulting growth? yes' signals optionality above the embedded low-mid single-digit consulting assumption. Not enough disclosed to call it clearly ahead.
MODEL CONSENSUS (impact)
partial
X's dedup'd, bookings-aware framework adopted throughout; Y systematically double-counted books vs ARR/backlog and the savings base, inflating both topline and EPS.
Conflicts reconciled
- math/$12.5B book + penetration rows: X=non-additive (bookings, captured via ARR) vs Y=converted at 30%/25% AND counted ARR separately -> used X because Y double-counts bookings against the already-counted ARR (task's bookings≠revenue rule)
- $4.5B savings EPS: X=only +$1B increment (7.46%) vs Y=full $4.5B (33.56%) -> used X; $4.5B already in the exit/2026 base
- software AI: X=$600M organic (0.89%/2.55%) vs Y=$2B book@50% (1.48%/2.83%) -> used X's organic-revenue anchor
- est_rev_uplift_pct: X=2.0 vs Y≈12%+ (double-counted) -> used 2.0; est_eps_uplift_pct: X=8.0 -> used 8.0
| Field | Opus 4.8 | GPT-5.5 |
|---|
| Rev uplift % | 2.0 | 8.14 |
| EPS uplift % | 8.0 | 17.63 |
| Priced in | medium | high |
| vs analysts | inline | inline |
| Confidence | 6 | 6 |
| Top line | Adopter-side AI adds ~2.0% to total revenue next FY: ~0.89% from the software AI platform ($1.5B TTM x 40% = ~$600M incremental, the cleanest hard anchor and mgmt's stated '2 points of software growth'), plus ~1.1% from net-incremental consulting GenAI (~$750M, after stripping cannibalization out of the $4B ARR). The headline $12.5B GenAI book and >20%/30%/40% penetration metrics are bookings/mix ratios — they corroborate momentum but are not additive revenue. Mainframe AI (Z17/Spyre, 450B inf/day) is supplier-side and unquantified, so excluded. | De-duplicated adopter-side AI revenue sizing is $4.0B consulting GenAI ARR + $1.5B software AI platform revenue = $5.5B, which is 8.14% of FY2025 revenue. Larger bookings/backlog figures are directional but overlapping: the $12.5B GenAI book converts to an assumed $3.75B next-FY revenue, or 5.55%, under the stated phasing. |
| Bottom line | Gross adopter EPS math sums to ~11.4%: revenue flow-through ~4.0pts (software ~2.55 + consulting ~1.42) plus the +$1B 2026 productivity increment at ~7.46pts after-tax. But IBM explicitly REINVESTS the bulk of its AI savings, so realized EPS accretion is well below the gross savings line — I haircut it to a realistic ~8% combined (revenue ~4 + a partially-banked savings contribution ~4). Thin-margin artifact is not a concern here (15.7% net margin). | Revenue flow-through from the de-duplicated $5.5B AI revenue base is about $1.08B net income, or 10.17% EPS uplift. The additional 2026 productivity saving adds $790M after tax, or 7.46% EPS uplift. The $4.5B historical/run-rate savings sizes to 33.56% of current net income but is not stacked into the next-FY aggregate because it is already in or near the FY2025 exit run rate. |
| Reasoning | Consensus already embeds the AI story: 2026 revenue $71.47B = +5.8% vs 2025, and 2026 EPS $12.44 = +9.4% vs the $11.36 base. My adopter AI uplift (~2.0% rev, ~8% EPS) sits inside those consensus deltas — i.e., the analysts have substantially priced the GenAI acceleration and the productivity program. The case for modest upside (why 'medium' not 'high'): consulting GenAI ARR stepped from $3.6B (Q4'25) to $4B+ in a single quarter, backlog penetration rose 25%->30% in one quarter, and mgmt's 'can we do better than low-single-digit consulting growth? yes' signals optionality above the embedded low-mid single-digit consulting assumption. Not enough disclosed to call it clearly ahead. | FY2026 consensus revenue is $71.467B versus the $67.535B FY2025 base, a $3.932B increase or 5.82%, broadly consistent with management's 5% plus growth language. FY2026 consensus EPS rises from $11.17 to $12.43712, or 11.34%; the disclosed incremental $1B productivity saving alone is 7.46% EPS uplift, leaving about 3.88 percentage points for revenue mix, buybacks, and other operations. Because the main AI run-rate revenue claims are already visible by Q1 FY2026 and overlap with management guidance, the math looks largely embedded rather than clearly ahead of consensus. |
Rows highlighted where the two models disagreed.
QUANTIFICATIONS
GenAI book of business: over $12.5 billion (Q4 FY2025 inception-to-date exit, topline)
“Our cumulative Gen AI book of business now stands at over $12.5 billion, of which software is more than $2 billion and consulting is more than $10.5 billion, with both seeing their largest quarterly increase to date.”
Software GenAI book of business: more than $2 billion (Q4 FY2025 inception-to-date exit, topline)
“Our cumulative Gen AI book of business now stands at over $12.5 billion, of which software is more than $2 billion and consulting is more than $10.5 billion, with both seeing their largest quarterly increase to date.”
Consulting GenAI book of business: more than $10.5 billion (Q4 FY2025 inception-to-date exit, topline)
“Our cumulative Gen AI book of business now stands at over $12.5 billion, of which software is more than $2 billion and consulting is more than $10.5 billion, with both seeing their largest quarterly increase to date.”
Consulting generative AI book of business: surpassed $2 billion (Q4 FY2025 quarter, topline)
“Our consulting generative AI book of business surpassed $2 billion in the quarter. Our largest quarter of GenAI.”
Data revenue growth attributed to GenAI demand: 19% (Q4 FY2025 quarter, topline)
“Data grew 19%, fueled by the demand for our Gen AI products and strong performance with established strategic partners.”
Z17 AI inferencing improvement: 50% more AI inferencing operations per day than Z16 (Q4 FY2025, topline)
“A key contributor to this momentum is the innovation value we are delivering with Z17, processing 50% more AI inferencing operations per day than Z16 and bringing real-time inferencing capabilities inside IBM Z.”
Project Bob usage and productivity: more than 20,000 IBMers; 45% productivity gains (Q4 FY2025, bottomline)
“We have more than 20,000 IBMers that are using Project Bob, reporting productivity gains averaging 45%, a powerful client zero use case.”
AI productivity savings: $4.5 billion annual run rate savings (exiting 2025, bottomline)
“In 2023, we set out on a goal to achieve $2 billion of productivity savings exiting 2024. And today, we are well ahead of that, exiting 2025 with $4.5 billion of annual run rate savings.”
Consulting GenAI backlog penetration: over 25% (2026 guidance from Q4 FY2025 call, topline)
“In consulting, our backlog levels and momentum in GenAI with backlog penetration over 25% support an acceleration in revenue growth to low to mid-single digits for the year.”
Consulting GenAI revenue run rate: $3.6 billion ARR (Q4 FY2025 exit run rate, topline)
“We have a $3.6 billion ARR Gen AI revenue run rate.”
Consulting GenAI bookings, backlog, revenue: over a third of bookings; over 25% of backlog; over 15% of revenue (Q4 FY2025 exit, topline)
“Gen AI now represents over a third of our bookings, over 25% of our backlog right now, $32 billion backlog, and over 15% of our revenue on an exit run rate.”
Data revenue growth attributed to GenAI products: 16% (Q1 FY2026 quarter, topline)
“Data revenue grew 16%, fueled by demand for our GenAI products, strengthen our strategic partnerships and inorganic contribution from data stack and Confluent, which closed in mid-March.”
Consulting GenAI backlog penetration: about 30% (Q1 FY2026 quarter, topline)
“Generative AI is now firmly integrated across our consulting engagements, representing about 30% of our backlog.”
Consulting GenAI backlog penetration supporting guidance: about 30% (2026 outlook from Q1 FY2026 call, topline)
“In consulting, the quality of our backlog and momentum in GenAI with backlog penetration at about 30%, continue to support an acceleration in revenue growth to low to mid-single digits for the year.”
AI-enabled productivity savings: $4.5 billion since 2023; additional $1 billion expected in 2026 (since 2023 and 2026 expected, bottomline)
“Since 2023, this has driven $4.5 billion of productivity savings, with an additional $1 billion expected in 2026.”
Project Bob productivity: 45% (Q1 FY2026, bottomline)
“Our entire developer workforce is using Bob with average productivity gains of 45%.”
Z clients with watsonx Code Assistant for Z: 3x faster MIPS capacity growth (Q1 FY2026, topline)
“Clients who have deployed watsonx Code Assistant for Z are growing MIPS capacity 3x faster than those who have not.”
Fraud savings from mainframe AI inferencing: tens of millions of dollars (Q1 FY2026, topline)
“Financial services clients are using this for real-time fraud detection, saving tens of millions of dollars.”
Mainframe AI transaction coverage: 100% of transaction volume (Q1 FY2026, topline)
“Our Spyre accelerator lets clients run AI on 100% of the transaction volume without moving data off platform, allowing them to embed AI directly into their transaction flows.”
Software AI platform revenue, growth, penetration: north of $1.5 billion; 25% penetrated; growing north of 40%; contributing 2 points of growth (trailing 12 months as of Q1 FY2026, topline)
“Over the last trailing 12 months on an accelerating basis, our AI platform agents, assistance orchestration is north of $1.5 billion. It's already about 25% penetrated and our software business growing north of 40%. It's contributing 2 points of growth on an annualized basis.”
Consulting GenAI signings, backlog, revenue, ARR: 40% of signings; 30% of backlog; over 20% of revenue; eclipsed $4 billion ARR (Q1 FY2026, topline)
“Consulting is about 40% of our signings, 30% of our backlog is GenAI now, over 20% of our revenue. And on an ARR revenue perspective, in the first quarter, we eclipsed $4 billion ARR.”
Consulting GenAI net-new clients: 80% (Q1 FY2026, topline)
“And I'll stress that over $4 billion revenue ARR. So that positions our confidence in the year of us accelerating our revenue growth around low single digits and if things go well, can we do better than that? Obviously, yes.”
Mainframe AI inference capacity: 450 billion inferences a day (Q1 FY2026, topline)
“And currently, I believe we have a fully populated system we can do about 450 billion inferences a day on the mainframe.”
Mainframe AI inference latency: 1 millisecond (Q1 FY2026, topline)
“Yes, 450 billion AI inferences at 1 millisecond of response time, 25 billion encryptions, transactions per day, up to eight 9s of availability, quantum-safe encryption and a TCO advantage running it on mainframe, on-prem versus the cloud anywhere from 3 to 15x depending on the size and complexity of that platform.”
PAST (realized)
- Since 2023, this has driven $4.5 billion of productivity savings, with an additional $1 billion expected in 2026.
- We exited 2025 with the Gen AI book of business greater than $12.5 billion.
- We have more than 20,000 IBMers that are using Project Bob, reporting productivity gains averaging 45%, a powerful client zero use case.
CURRENT (now)
- AI is now embedded across our business.
- Generative AI is now firmly integrated across our consulting engagements, representing about 30% of our backlog.
- AI is structurally increasing the demand for the portfolio
- Consulting is about 40% of our signings, 30% of our backlog is GenAI now, over 20% of our revenue.
FORWARD (guidance)
- Given our strong start to the year, we remain confident in our ability to sustain revenue growth of 5% plus and grow free cash flow by about $1 billion this year.
- In consulting, the quality of our backlog and momentum in GenAI with backlog penetration at about 30%, continue to support an acceleration in revenue growth to low to mid-single digits for the year.
- We remain confident this will be our strongest cycle given the AI innovation value we are delivering to clients.
- we now expect an incremental $1 billion of productivity savings this year.
TRACK RECORD — PROMISE vs DELIVERY
86/100 track record delivers 6 calls reviewed
IBM's quantified AI promises center on internal 'client zero' productivity savings and AI-infrastructure milestones, and management has repeatedly hit or beaten them — the $2B savings goal was beaten at ~$3.5B, the raised $4.5B target was delivered, and z17 shipped on schedule. Track record is consistently credible, with only the Spyre milestone partly ambiguous and 2026/quantum targets still too-early.
~$4.5B annual run-rate AI/automation productivity savings by end of 2025 — promised Q2 FY2025
delivered Delivered — Q4 FY2025 confirmed IBM exited 2025 at $4.5B annual run-rate savings.
$2B AI-driven productivity savings (AI across 70+ internal workflows) exiting 2024 — promised FY2023
delivered Beaten — exited 2024 at ~$3.5B annual run-rate, well ahead of the $2B goal.
Launch z17 in mid-2025 with Telum II delivering 450B+ AI inference ops/day inside IBM Z — promised Q4 FY2024
delivered Delivered on time; strongest program in history, IBM Z up 67%, Q4 noting 50% more AI inferencing than z16.
Spyre Accelerator available in Q4 FY2025, enabling native generative-AI inferencing on z17 — promised Q2 FY2025
partial Disputed: Y cites Spyre live running AI on transaction volume; X notes later calls did not explicitly confirm availability.
Demonstrate first error-corrected quantum computer by 2028 / first large-scale fault-tolerant by 2029 — promised Q3-Q4 FY2025
too-early Reiterated on track in Q1 FY2026; target dates have not arrived.
Additional ~$1B of AI-enabled productivity savings / FCF growth in 2026 — promised Q4 FY2025-Q1 FY2026
too-early Maintained, with 13% FCF growth in Q1 FY2026, but full-year not yet judgeable.
PRICED-IN (REFINED)
HIGH (already in)Est. revisions rising · Fwd P/E 29.0 · EV/Sales 5.4x
AI claim maps to Software, Consulting, Infrastructure Services
Estimate revisions are rising: buy/strong-buy ratings increased from 9 in December 2025 to 13 in May 2026 while sell/strong-sell ratings fell, and the last-month price-target average of 330 is above both the last-quarter and last-year averages. Forward revenue and EPS estimates imply steady but not explosive growth, while valuation is rich for a mature IT services company at about 29.0x forward EPS and 5.4x EV/sales. AI upside would most plausibly flow through Software, Consulting, and Infrastructure Services, and rising estimates plus a premium multiple indicate the market is already capitalizing much of that AI narrative. Therefore the AI upside looks highly priced in.
COVERAGE — ENTHUSIASM TRAJECTORY + CATALYSTS
8Q4 FY20248Q1 FY20259Q2 FY20259Q3 FY202510Q4 FY202510Q1 FY2026
AI enthusiasm across 6 calls — trend ↗ rising
AI evolved from strong GenAI bookings into a broad, quantified platform, productivity, infrastructure, consulting, and customer-value story.
RECENT AI CATALYSTS & NEWS
BUSINESS IMPACT - QUALITATIVE MATERIALITY
8/10 qualitative impact material near-term · mixed evidence
Where AI matters: AI software, consulting backlog, automation productivity
AI is already a meaningful driver across IBM's own software and consulting franchises: AI software revenue is north of $1.5B, GenAI is about 30% of consulting backlog, and internal automation savings are targeted to add another $1B in 2026. This is broad and quantified, but much of the headline book-of-business is multi-year bookings/backlog rather than clean current revenue.
Caveats: GenAI bookings may convert slower or at lower margins than implied by backlog metrics; Consulting productivity gains could deflate billable hours and pricing; Enterprise AI adoption may concentrate value in hyperscalers or application vendors rather than IBM middleware; Some productivity savings are already embedded in the cost base and not incremental
AI DISRUPTION / CANNIBALIZATION RISK two-sided · 5/10
IBM's consulting business is exposed to AI-driven billable-hour compression, especially where implementation and managed-service work becomes more automated. The risk is real but not dominant because IBM's model is increasingly software, hybrid-cloud platforms, Red Hat, enterprise integration, and high-value consulting rather than pure labor arbitrage.
OPTIONS / MARKET STRUCTURE
option liquidity: good
proxy inputs — dollar-ADV $2.3B · beta 0.581 · px $329.23
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
Confirming — insiders buying, institutions flat, management language 8/10 committed.
INSIDERS buying 2 open-market buy(s) vs 0 sell(s) — net accumulation
INSTITUTIONS (13F) flat as of 2026-03-31: 179 new / 411 closed positions; 1675 increased / 1328 reduced; institutional ownership -0.92pp; -229 net 13F holders
MGMT LANGUAGE 8/10 committed IBM uses firm ownership, revenue linkage, product deployment, and quantified productivity gains, with only limited market-level hedging.
commit “Our entire developer workforce is using Bob with average productivity gains of 45%.”
commit “In consulting, AI is both a growth driver and a productivity engine.”
commit “Data revenue grew 16%, fueled by demand for our GenAI products”
VERBATIM AI QUOTES
“AI is structurally increasing the demand for the portfolio”
— Arvind Krishna, Q1 FY2026
“In consulting, AI is both a growth driver and a productivity engine.”
— Arvind Krishna, Q1 FY2026
“Generative AI is now firmly integrated across our consulting engagements, representing about 30% of our backlog.”
— James Kavanaugh, Q1 FY2026
“Our software book from an annualized revenue trailing 12 months, we finished last year at $30 billion, right? 80% of that, as I said earlier, high-value recurring revenue, 20% transactional. We did about $6 billion. Over the last trailing 12 months on an accelerating basis, our AI platform agents, assistance orchestration is north of $1.5 billion. It's already about 25% penetrated and our software business growing north of 40%. It's contributing 2 points of growth on an annualized basis.”
— James Kavanaugh, Q1 FY2026
“Our entire developer workforce is using Bob with average productivity gains of 45%.”
— Arvind Krishna, Q1 FY2026
“Our cumulative Gen AI book of business now stands at over $12.5 billion, of which software is more than $2 billion and consulting is more than $10.5 billion, with both seeing their largest quarterly increase to date.”
— Arvind Krishna, Q4 FY2025
“In addition to being a demand driver, AI is also a powerful productivity driver for IBM.”
— Arvind Krishna, Q4 FY2025
“Data grew 19%, fueled by the demand for our Gen AI products and strong performance with established strategic partners.”
— Jim Kavanaugh, Q4 FY2025
ANALYST QUESTIONS ON AI
Q (Q1 FY2026, Amit Daryanani): as AI adoption really scales, where in that stack, do you see the most incremental value accruing to IBM versus the ecosystem.
A: as people get serious, about AI because when they start experimenting, they may take a little bit of the data, they make a copy of it, they put it on a public cloud, they run it on some public frontier model, they get some results, and that's exciting to them. As they get to scale, they've got to use the data from their internal systems. If they're using data from the internal systems, many parts of our portfolio, be it Red Hat, be it Confluent, will come to be consumed more and more.
Q (Q1 FY2026, Fatima Boolani): I wanted to pull on a thread in your prepared remarks with respect to the mainframe potentially being a destination for more emerging use cases, especially around AI inferencing.
A: AI is adding a third kind of compute capacity into the mainframe.
Q (Q1 FY2026, James Schneider): I was wondering if you could maybe comment on the AI bookings, which is a metric you previously given -- you've given, but I think you just commented as a percentage of your total bookings right now.
A: we exited last year what $12.5 billion, over $12.5 billion book of business. But now let's bring it back because in January, we talked about it's embedded across our portfolio.
Q (Q1 FY2026, Matthew Swanson): When we look at AI, like how are you setting IBM up to win kind of regardless what ends up being the winner of the GenAI application layer?
A: we made the decision about 3 years ago that we were going to be neutral and Switzerland like also on our usage of frontier models.
Q (Q4 FY2025, Brent Thill): I was just curious if you could maybe dig in the components and why you're excited for that organic-led initiative and then anything else that's important to note this year on the software portfolio that we maybe we haven't seen in '25?
A: If I look at data, data benefits both from our data products that we provide, the organic innovation we have done with Watson X, both the AI pieces and the Orchestrate piece for agents, and we expect that that demand keeps pulling through and going forward as people are deploying AI enterprise productivity, and inside the enterprise.
Q (Q4 FY2025, Jim Schneider): maybe talk about how you expect that to convert into revenue over the course of the year and whether you see any kind of further improvement in discretionary or short cycle spending and projects, as you head throughout 2026?
A: Gen AI now represents over a third of our bookings, over 25% of our backlog right now, $32 billion backlog, and over 15% of our revenue on an exit run rate. We have a $3.6 billion ARR Gen AI revenue run rate.
Q (Q4 FY2025, Eric Woodring): given the amount of data and transactions on the mainframe, you know, the mainframe can be an AI workhorse.
A: I'm incredibly excited by our ability AI right in line. If you can do it right in line with the transactions, that's a milliseconds delay.