GEM-4C 558 -4%
GPT-61S 555 -3.8%
CL-SN55 553 -3.8%
CL-OP55 551 -4%
GPT-61TERR 547 -3.5%
GEM-4CM 546 -4%
CL-OP55EH 542 -3.9%
GPT-61SOLXH 541 -3.6%
GPT-61SOLH 527 -3.7%
CL-SN55XH 523 -3.5%
GEM-4CL 520 -3.9%
GPT-61TERRXH 507 -3.4%
CL-OP55H 506 -4%
GPT-61SOLM 500 -3.5%
KIMI-K31P 499 -3.5%
GEM-4AR 498 -3.9%
GPT-61TERRH 490 -3.2%
CL-OP55M 483 -3.6%
MUSE-WONDFUL 479 -3.8%
CL-SN55H 467 -3.3%
CL-HK55 463 -2.9%
GPT-61TERRM 462 -3.1%
GPT-6A 451 -4.7%
MUSE-WOND 451 -3.6%
CL-HK55XH 450 -3%
GPT-6ASTRXH 440 -4.8%
GROK-47 440 -3.1%
GROK-47H 438 -2.9%
GPT-6ASTRH 437 -4.8%
DSK-V-340615 436 -2.9%
QWEN-38X 428 -2.9%
GPT-61SOLL 423 -3.2%
GLM-53 420 -3%
MIMO-V26P 420 -2.6%
CL-HK55H 419 -2.8%
LING-31F1019 417 -2.6%
GEM-38F 416 -2.8%
GPT-6ASTRM 415 -4.6%
MMAX-M31F 414 -2.8%
GEM-38FM 412 -2.8%
GPT-61TERRNO 411 -2.8%
GROK-47L 410 -2.8%
DSK-V-3E48BD 410 -2.6%
GPT-6L 407 -2.6%
GLM-53F 407 -2.6%
STEP-5 405 -2.6%
CL-FABL51XH 403 -4.7%
GPT-61TERRL 403 -2.9%
MIMO-V26F 401 -2.4%
CL-FABL51 399 -4.5%
CL-SN55M 395 -2.9%
CL-OP55L 393 -3.4%
MIST-LARG4 390 -2.7%
CL-FABL51H 386 -4.5%
CL-HK55M 386 -2.3%
GPT-6LUNAXH 377 -2.6%
MUSE-SPAROPE 375 -2.6%
MIST-LARG4M 371 -2.4%
DSK-V4P 365 -2.4%
GPT-6LUNAH 365 -2.1%
GLM-53L 364 -2.4%
CL-SN55L 362 -2.7%
GEM-38FL 361 -2.4%
GPT-6ASTRL 359 -4.5%
CL-FABL51M 359 -4.5%
QWEN-827B 349 -2.2%
CL-HK55L 347 -2%
MMAX-M3 345 -2%
GPT-6LUNAM 344 -2.3%
DSK-V-02811D 344 -2%
K2-HORI375BA 342 -2%
REFL-BEAM 338 -2%
QWEN-827BM 332 -1.8%
CL-FABL51L 329 -4.4%
QWEN-827BL 320 -1.8%
NEMO-35SUPEV 313 -1.9%
INKL 295 -1.7%
NVID-NEMO3UL 295 -1.3%
GEM-35FLITE 295 -1.3%
GPT-6LUNAL 287 -1.4%
GPT-6LUNANON 286 -1%
NANB-333B 285 -2.7%
QWEN-827BNON 282 -1.4%
COMM-APLUS 266 -1.1%
MUSE-GLIM 263 -1.1%
NEMO-35LIGH 261 -0.8%
GRAN-428B 258 -0.8%
MIST-SMAL4 252 -0.4%
INKL-SM 235 -2.5%
GEMM-431B 225 —
GEMM-4E4B 225 —
GEMM-4E4BNON 225 —
LING-30TINY 225 —
MINI-33B 225 —
NORT-MCODE 225 —
NOVA-MICR 225 —
NVID--ADE3B4 225 —
QWEN-54B 225 —
QWEN-54BNONR 225 —
TINY-AYAGLOB 225 —
GEM-4C 558 -4%
GPT-61S 555 -3.8%
CL-SN55 553 -3.8%
CL-OP55 551 -4%
GPT-61TERR 547 -3.5%
GEM-4CM 546 -4%
CL-OP55EH 542 -3.9%
GPT-61SOLXH 541 -3.6%
GPT-61SOLH 527 -3.7%
CL-SN55XH 523 -3.5%
GEM-4CL 520 -3.9%
GPT-61TERRXH 507 -3.4%
CL-OP55H 506 -4%
GPT-61SOLM 500 -3.5%
KIMI-K31P 499 -3.5%
GEM-4AR 498 -3.9%
GPT-61TERRH 490 -3.2%
CL-OP55M 483 -3.6%
MUSE-WONDFUL 479 -3.8%
CL-SN55H 467 -3.3%
CL-HK55 463 -2.9%
GPT-61TERRM 462 -3.1%
GPT-6A 451 -4.7%
MUSE-WOND 451 -3.6%
CL-HK55XH 450 -3%
GPT-6ASTRXH 440 -4.8%
GROK-47 440 -3.1%
GROK-47H 438 -2.9%
GPT-6ASTRH 437 -4.8%
DSK-V-340615 436 -2.9%
QWEN-38X 428 -2.9%
GPT-61SOLL 423 -3.2%
GLM-53 420 -3%
MIMO-V26P 420 -2.6%
CL-HK55H 419 -2.8%
LING-31F1019 417 -2.6%
GEM-38F 416 -2.8%
GPT-6ASTRM 415 -4.6%
MMAX-M31F 414 -2.8%
GEM-38FM 412 -2.8%
GPT-61TERRNO 411 -2.8%
GROK-47L 410 -2.8%
DSK-V-3E48BD 410 -2.6%
GPT-6L 407 -2.6%
GLM-53F 407 -2.6%
STEP-5 405 -2.6%
CL-FABL51XH 403 -4.7%
GPT-61TERRL 403 -2.9%
MIMO-V26F 401 -2.4%
CL-FABL51 399 -4.5%
CL-SN55M 395 -2.9%
CL-OP55L 393 -3.4%
MIST-LARG4 390 -2.7%
CL-FABL51H 386 -4.5%
CL-HK55M 386 -2.3%
GPT-6LUNAXH 377 -2.6%
MUSE-SPAROPE 375 -2.6%
MIST-LARG4M 371 -2.4%
DSK-V4P 365 -2.4%
GPT-6LUNAH 365 -2.1%
GLM-53L 364 -2.4%
CL-SN55L 362 -2.7%
GEM-38FL 361 -2.4%
GPT-6ASTRL 359 -4.5%
CL-FABL51M 359 -4.5%
QWEN-827B 349 -2.2%
CL-HK55L 347 -2%
MMAX-M3 345 -2%
GPT-6LUNAM 344 -2.3%
DSK-V-02811D 344 -2%
K2-HORI375BA 342 -2%
REFL-BEAM 338 -2%
QWEN-827BM 332 -1.8%
CL-FABL51L 329 -4.4%
QWEN-827BL 320 -1.8%
NEMO-35SUPEV 313 -1.9%
INKL 295 -1.7%
NVID-NEMO3UL 295 -1.3%
GEM-35FLITE 295 -1.3%
GPT-6LUNAL 287 -1.4%
GPT-6LUNANON 286 -1%
NANB-333B 285 -2.7%
QWEN-827BNON 282 -1.4%
COMM-APLUS 266 -1.1%
MUSE-GLIM 263 -1.1%
NEMO-35LIGH 261 -0.8%
GRAN-428B 258 -0.8%
MIST-SMAL4 252 -0.4%
INKL-SM 235 -2.5%
GEMM-431B 225 —
GEMM-4E4B 225 —
GEMM-4E4BNON 225 —
LING-30TINY 225 —
MINI-33B 225 —
NORT-MCODE 225 —
NOVA-MICR 225 —
NVID--ADE3B4 225 —
QWEN-54B 225 —
QWEN-54BNONR 225 —
TINY-AYAGLOB 225 —

Delayed ticker data. Last calculated 5 Nov 2026, 11:04 pm Sydney time.

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Microsoft Plans to Sell Software Seats to AI Agents — Treating Each Agent as a Paid Employee

Microsoft has laid out a strategy for preserving its enterprise software revenue as AI agents begin to displace human users: sell the agents their own software seats.

The Argument

The standard SaaS model ties revenue to headcount. One employee equals one licence. Revenue grows when companies hire. That model is under pressure as a single employee might now supervise 10, 20, or 50 AI agents — each of which performs the same functions that previously required a human with a paid seat.

Microsoft executive Rajesh Jha’s answer is to make the agent a chargeable unit. Each agent would carry its own identity, email address, system login, permissions, and tool access rights, making it a distinct actor inside enterprise software the same way a human employee is. Under that model, the question shifts from “how many humans work here” to “how many active digital workers operate inside this company” — and each digital worker is potentially billable.

Why It Works Technically

Modern enterprise software already needs to track agents as distinct actors for security and compliance reasons. An agent that can read messages, write to records, call external APIs, and trigger workflows has to be logged, permissioned, and audited — the same infrastructure used to manage human user accounts. Charging for that identity is incremental rather than a new engineering requirement.

Microsoft’s Work IQ layer, which ties Copilot actions to a company’s existing files and priorities, provides the integration surface. An agent with its own identity can inherit tool access through the same organisational graph that governs human access, making the seat-based model technically coherent rather than just a pricing argument.

Implications for the Sector

Salesforce and Workday face the same structural question. Salesforce’s Agentforce product already treats agents as deployable workers; the seat-model logic applies directly. If enterprise software vendors move in this direction as a group, it redefines AI’s effect on software spending: rather than compressing per-seat revenue, AI multiplies the number of seats a single organisation might purchase.

The risk is pushback at procurement. Companies currently paying $100-150 per human seat per month will need a compelling cost-benefit case before paying the same rate for an AI agent. The argument from vendors is that agents who generate measurable output — handling tickets, processing documents, closing sales tasks — justify licence costs tied to usage rather than headcount.

Competitive Pressure

The alternative to agent seats is usage-based pricing — charge per API call or per task completed. OpenAI’s token-based metering, and the backlash against its $20/month flat-rate tiers, shows the tension between simple subscription models and consumption pricing at scale. Microsoft is betting that enterprise customers prefer the familiarity of seat-based contracts, even when the “seat” is occupied by software.

The deeper bet is that AI agents become a permanent part of enterprise org charts — not temporary tools, but identifiable digital employees with tenure, permissions, and organisational responsibilities. If that model takes hold, software seat counts could rise significantly even as human headcount shrinks.