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ATL280

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	= ATL280: Proposed AICPA-IRS Tax AI Risk Framework =		= ATL280: Proposed AICPA-IRS Tax AI Risk Framework =
	* Episode: ATL280		* Episode: ATL280

File:ATL280.jpg

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ATL280 Proposed AICPA-IRS Tax AI Risk Framework

ATL280

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Companies, organizations, products, and services mentioned

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	= ATL280: Proposed AICPA-IRS Tax AI Risk Framework = * Episode: ATL280 * Podcast: Accounting Technology Lab * Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA * Recorded: October 2, 2026 * Published: October 23, 2026 * Duration: Approximately 25 minutes * Presented by: CPA Practice Advisor == Episode summary == Artificial intelligence is changing tax preparation, but who is responsible when the technology gets it wrong? In Episode 280 of the Accounting Technology Lab, Randy Johnston and Brian Tankersley examine a proposed AI tax risk framework discussed in materials associated with former IRS Commissioner Danny Werfel. They focus on five categories of risk for tax preparers: technical, practice, legal and regulatory, business, and workforce and strategic. The hosts examine AI hallucinations, inaccurate document extraction, client data leakage, overtrust of AI-generated tax advice, and erosion of professional expertise. They also explain how AI-driven productivity can overwhelm conventional human review procedures. Other concerns include shadow AI, professional liability, client disclosure, vendor dependence, and preservation of institutional knowledge. The discussion distinguishes risks faced by practitioners from risks facing tax authorities, identifying hallucinations, overtrust, skill erosion, data leakage, and vendor dependence as overlapping concerns. The practical message is that faster preparation does not eliminate professional accountability. Firms need independent verification, appropriate human oversight, reliable source documentation, protection of confidential taxpayer information, and thoughtful AI governance. The framework is discussed as a proposal, not as a binding new IRS rule. == Key takeaways == * Verify AI tax conclusions against authoritative sources. * Preserve meaningful human review even as AI throughput increases. * Protect taxpayer information from unauthorized tools and vendors. * Clarify professional liability, disclosure, and governance responsibilities. * Maintain tax expertise and contingency plans for vendor dependence. == Quotable moments == {\| class="wikitable" ! Time !! Speaker !! Transcript excerpt \|- \| 05:55 \|\| Brian Tankersley \|\| “The hope here is ... that they’re going to keep their weeds level knowledge of this and not just outsource the whole thing to AI.” \|- \| 07:38 \|\| Brian Tankersley \|\| “Just imagine a TikTok tax advice.” \|- \| 11:29 \|\| Randy Johnston \|\| “The AI answers are being gained by people who have certain messages they want to appear.” \|- \| 12:34 \|\| Brian Tankersley \|\| “The scary part about it, though, is that many people don’t go back and look at primary sources.” \|- \| 14:20 \|\| Randy Johnston \|\| “More returns get processed with less scrutiny.” \|- \| 19:09 \|\| Brian Tankersley \|\| “The AI is supremely confident all the time.” \|- \| 24:00 \|\| Randy Johnston \|\| “I think it’s a must-read for anybody that’s in practice.” \|} == Social media posts == === 1. LinkedIn === AI is changing tax preparation. But when AI gets the tax law wrong, who is responsible? ATL280 explores the proposed AI tax risk framework. #TaxAI #ATL280 === 2. LinkedIn === Skill erosion may be the AI risk firms underestimate. Can your staff catch an AI-generated tax mistake? #TaxProfessionals #ATL280 === 3. LinkedIn === AI agents can prepare work in parallel. Human review is still a bottleneck. How should firms respond? #AccountingAI #ATL280 === 4. LinkedIn === One AI error can threaten years of client trust. Learn why disclosure and review matter. #TaxPractice #ATL280 === 5. LinkedIn === A confident AI answer is not authoritative tax guidance. Verify the primary sources. #TaxResearch #ATL280 === 6. X === AI can prepare a return. Can it defend the tax position? #TaxAI #ATL280 === 7. X === AI can be confidently wrong. Tax professionals need independent verification. #ATL280 === 8. X === More returns. Faster processing. Less review? That is not automatically progress. #ATL280 === 9. X === Shadow AI and confidential tax data are a dangerous combination. #DataPrivacy #ATL280 === 10. X === Your AI vendor may change. Your professional responsibility does not. #ATL280 === 11. Facebook === AI makes tax preparation faster, but does it make it safer? ATL280 explores five categories of risk. === 12. Facebook === Are we losing the tax expertise needed to catch AI errors? Randy and Brian discuss skill erosion in ATL280. === 13. Facebook === Would you trust a tax answer just because it sounds confident? Explore AI hallucinations and overtrust in ATL280. === 14. Facebook === What happens when one AI tax error affects hundreds of clients? ATL280 examines professional liability and reputational risk. === 15. Facebook === Your employees may already use unapproved AI tools. ATL280 discusses shadow AI and client data. === 16. Instagram === AI is fast. Tax law is complicated. Professional judgment matters. #TaxAI #ATL280 === 17. Instagram === Five AI risk categories. One question: Who checks the AI? #ATL280 === 18. Instagram === Hallucinations. Overtrust. Data leakage. Skill erosion. Vendor dependence. #ATL280 === 19. Instagram === AI sounds confident. Your tax research still needs authoritative sources. #TaxResearch #ATL280 === 20. Instagram === Do not let AI turn your review process into a rubber stamp. #AccountingAI #ATL280 == Companies, organizations, products, and services mentioned == {\| class="wikitable" ! Name !! Context !! X !! Facebook !! LinkedIn !! Instagram \|- \| AICPA \|\| Framework context \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|- \| Internal Revenue Service (IRS) \|\| Tax authority and risk framework context \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|- \| CPA Practice Advisor \|\| Podcast presenter \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|- \| The Tax Adviser \|\| Article about the proposed framework \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|- \| ChatGPT / OpenAI \|\| Example of generative AI output risk \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|- \| KPMG \|\| Mention of simulation-style professional training \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|- \| Tesla \|\| Autonomous driving liability analogy \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|- \| Wikipedia \|\| AI source reliability discussion \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|- \| TikTok \|\| Tax advice analogy \|\| Not verified \|\| Not verified \|\| Not verified \|\| Not verified \|} == Editorial and sourcing notes == * Based on the October 23, 2026 episode transcript and timestamped SRT. * Framework discussed as proposed; this page does not claim it is a binding IRS regulation. * Social media handles are intentionally not supplied without verification. * Timestamp labels are approximate segment start times~~. * No episode streaming URL or official slide deck URL was supplied~~.		= ATL280: Proposed AICPA-IRS Tax AI Risk Framework =
			* Episode: ATL280
			* Podcast: Accounting Technology Lab
			* Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA
			* Recorded: October 2, 2026
			* Published: October 23, 2026
			* Duration: Approximately 25 minutes
			* Presented by: CPA Practice Advisor

			== Episode summary ==
			Artificial intelligence is changing tax preparation, but who is responsible when the technology gets it wrong? In Episode 280 of the Accounting Technology Lab, Randy Johnston and Brian Tankersley examine a proposed AI tax risk framework discussed in materials associated with former IRS Commissioner Danny Werfel. They focus on five categories of risk for tax preparers: technical, practice, legal and regulatory, business, and workforce and strategic. The hosts examine AI hallucinations, inaccurate document extraction, client data leakage, overtrust of AI-generated tax advice, and erosion of professional expertise. They also explain how AI-driven productivity can overwhelm conventional human review procedures. Other concerns include shadow AI, professional liability, client disclosure, vendor dependence, and preservation of institutional knowledge. The discussion distinguishes risks faced by practitioners from risks facing tax authorities, identifying hallucinations, overtrust, skill erosion, data leakage, and vendor dependence as overlapping concerns. The practical message is that faster preparation does not eliminate professional accountability. Firms need independent verification, appropriate human oversight, reliable source documentation, protection of confidential taxpayer information, and thoughtful AI governance. The framework is discussed as a proposal, not as a binding new IRS rule.

			== Key takeaways ==
			* Verify AI tax conclusions against authoritative sources.
			* Preserve meaningful human review even as AI throughput increases.
			* Protect taxpayer information from unauthorized tools and vendors.
			* Clarify professional liability, disclosure, and governance responsibilities.
			* Maintain tax expertise and contingency plans for vendor dependence.

			== Quotable moments ==
			{\| class="wikitable"
			! Time !! Speaker !! Transcript excerpt
			\|-
			\| 05:55 \|\| Brian Tankersley \|\| “The hope here is ... that they’re going to keep their weeds level knowledge of this and not just outsource the whole thing to AI.”
			\|-
			\| 07:38 \|\| Brian Tankersley \|\| “Just imagine a TikTok tax advice.”
			\|-
			\| 11:29 \|\| Randy Johnston \|\| “The AI answers are being gained by people who have certain messages they want to appear.”
			\|-
			\| 12:34 \|\| Brian Tankersley \|\| “The scary part about it, though, is that many people don’t go back and look at primary sources.”
			\|-
			\| 14:20 \|\| Randy Johnston \|\| “More returns get processed with less scrutiny.”
			\|-
			\| 19:09 \|\| Brian Tankersley \|\| “The AI is supremely confident all the time.”
			\|-
			\| 24:00 \|\| Randy Johnston \|\| “I think it’s a must-read for anybody that’s in practice.”
			\|}

			== Social media posts ==
			=== 1. LinkedIn ===
			AI is changing tax preparation. But when AI gets the tax law wrong, who is responsible? ATL280 explores the proposed AI tax risk framework. #TaxAI #ATL280

			=== 2. LinkedIn ===
			Skill erosion may be the AI risk firms underestimate. Can your staff catch an AI-generated tax mistake? #TaxProfessionals #ATL280

			=== 3. LinkedIn ===
			AI agents can prepare work in parallel. Human review is still a bottleneck. How should firms respond? #AccountingAI #ATL280

			=== 4. LinkedIn ===
			One AI error can threaten years of client trust. Learn why disclosure and review matter. #TaxPractice #ATL280

			=== 5. LinkedIn ===
			A confident AI answer is not authoritative tax guidance. Verify the primary sources. #TaxResearch #ATL280

			=== 6. X ===
			AI can prepare a return. Can it defend the tax position? #TaxAI #ATL280

			=== 7. X ===
			AI can be confidently wrong. Tax professionals need independent verification. #ATL280

			=== 8. X ===
			More returns. Faster processing. Less review? That is not automatically progress. #ATL280

			=== 9. X ===
			Shadow AI and confidential tax data are a dangerous combination. #DataPrivacy #ATL280

			=== 10. X ===
			Your AI vendor may change. Your professional responsibility does not. #ATL280

			=== 11. Facebook ===
			AI makes tax preparation faster, but does it make it safer? ATL280 explores five categories of risk.

			=== 12. Facebook ===
			Are we losing the tax expertise needed to catch AI errors? Randy and Brian discuss skill erosion in ATL280.

			=== 13. Facebook ===
			Would you trust a tax answer just because it sounds confident? Explore AI hallucinations and overtrust in ATL280.

			=== 14. Facebook ===
			What happens when one AI tax error affects hundreds of clients? ATL280 examines professional liability and reputational risk.

			=== 15. Facebook ===
			Your employees may already use unapproved AI tools. ATL280 discusses shadow AI and client data.

			=== 16. Instagram ===
			AI is fast. Tax law is complicated. Professional judgment matters. #TaxAI #ATL280

			=== 17. Instagram ===
			Five AI risk categories. One question: Who checks the AI? #ATL280

			=== 18. Instagram ===
			Hallucinations. Overtrust. Data leakage. Skill erosion. Vendor dependence. #ATL280

			=== 19. Instagram ===
			AI sounds confident. Your tax research still needs authoritative sources. #TaxResearch #ATL280

			=== 20. Instagram ===
			Do not let AI turn your review process into a rubber stamp. #AccountingAI #ATL280

			== Editorial and sourcing notes ==
			* Based on the October 23, 2026 episode transcript and timestamped SRT.
			* Framework discussed as proposed; this page does not claim it is a binding IRS regulation.
			* Timestamp labels are approximate segment start times.

ATL280

Bftcpa606 — Fri, 23 Oct 2026 12:49:51 GMT

Created page with "= ATL280: Proposed AICPA-IRS Tax AI Risk Framework = * Episode: ATL280 * Podcast: Accounting Technology Lab * Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA * Recorded: October 2, 2026 * Published: October 23, 2026 * Duration: Approximately 25 minutes * Presented by: CPA Practice Advisor == Episode summary == Artificial intelligence is changing tax preparation, but who is responsible when the technology gets it wrong? In Episode 280 of the Accounting Techn..."

New page

= ATL280: Proposed AICPA-IRS Tax AI Risk Framework = * Episode: ATL280 * Podcast: Accounting Technology Lab * Hosts: Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA * Recorded: October 2, 2026 * Published: October 23, 2026 * Duration: Approximately 25 minutes * Presented by: CPA Practice Advisor == Episode summary == Artificial intelligence is changing tax preparation, but who is responsible when the technology gets it wrong? In Episode 280 of the Accounting Technology Lab, Randy Johnston and Brian Tankersley examine a proposed AI tax risk framework discussed in materials associated with former IRS Commissioner Danny Werfel. They focus on five categories of risk for tax preparers: technical, practice, legal and regulatory, business, and workforce and strategic. The hosts examine AI hallucinations, inaccurate document extraction, client data leakage, overtrust of AI-generated tax advice, and erosion of professional expertise. They also explain how AI-driven productivity can overwhelm conventional human review procedures. Other concerns include shadow AI, professional liability, client disclosure, vendor dependence, and preservation of institutional knowledge. The discussion distinguishes risks faced by practitioners from risks facing tax authorities, identifying hallucinations, overtrust, skill erosion, data leakage, and vendor dependence as overlapping concerns. The practical message is that faster preparation does not eliminate professional accountability. Firms need independent verification, appropriate human oversight, reliable source documentation, protection of confidential taxpayer information, and thoughtful AI governance. The framework is discussed as a proposal, not as a binding new IRS rule. == Key takeaways == * Verify AI tax conclusions against authoritative sources. * Preserve meaningful human review even as AI throughput increases. * Protect taxpayer information from unauthorized tools and vendors. * Clarify professional liability, disclosure, and governance responsibilities. * Maintain tax expertise and contingency plans for vendor dependence. == Quotable moments == {| class="wikitable" ! Time !! Speaker !! Transcript excerpt |- | 05:55 || Brian Tankersley || “The hope here is ... that they’re going to keep their weeds level knowledge of this and not just outsource the whole thing to AI.” |- | 07:38 || Brian Tankersley || “Just imagine a TikTok tax advice.” |- | 11:29 || Randy Johnston || “The AI answers are being gained by people who have certain messages they want to appear.” |- | 12:34 || Brian Tankersley || “The scary part about it, though, is that many people don’t go back and look at primary sources.” |- | 14:20 || Randy Johnston || “More returns get processed with less scrutiny.” |- | 19:09 || Brian Tankersley || “The AI is supremely confident all the time.” |- | 24:00 || Randy Johnston || “I think it’s a must-read for anybody that’s in practice.” |} == Social media posts == === 1. LinkedIn === AI is changing tax preparation. But when AI gets the tax law wrong, who is responsible? ATL280 explores the proposed AI tax risk framework. #TaxAI #ATL280 === 2. LinkedIn === Skill erosion may be the AI risk firms underestimate. Can your staff catch an AI-generated tax mistake? #TaxProfessionals #ATL280 === 3. LinkedIn === AI agents can prepare work in parallel. Human review is still a bottleneck. How should firms respond? #AccountingAI #ATL280 === 4. LinkedIn === One AI error can threaten years of client trust. Learn why disclosure and review matter. #TaxPractice #ATL280 === 5. LinkedIn === A confident AI answer is not authoritative tax guidance. Verify the primary sources. #TaxResearch #ATL280 === 6. X === AI can prepare a return. Can it defend the tax position? #TaxAI #ATL280 === 7. X === AI can be confidently wrong. Tax professionals need independent verification. #ATL280 === 8. X === More returns. Faster processing. Less review? That is not automatically progress. #ATL280 === 9. X === Shadow AI and confidential tax data are a dangerous combination. #DataPrivacy #ATL280 === 10. X === Your AI vendor may change. Your professional responsibility does not. #ATL280 === 11. Facebook === AI makes tax preparation faster, but does it make it safer? ATL280 explores five categories of risk. === 12. Facebook === Are we losing the tax expertise needed to catch AI errors? Randy and Brian discuss skill erosion in ATL280. === 13. Facebook === Would you trust a tax answer just because it sounds confident? Explore AI hallucinations and overtrust in ATL280. === 14. Facebook === What happens when one AI tax error affects hundreds of clients? ATL280 examines professional liability and reputational risk. === 15. Facebook === Your employees may already use unapproved AI tools. ATL280 discusses shadow AI and client data. === 16. Instagram === AI is fast. Tax law is complicated. Professional judgment matters. #TaxAI #ATL280 === 17. Instagram === Five AI risk categories. One question: Who checks the AI? #ATL280 === 18. Instagram === Hallucinations. Overtrust. Data leakage. Skill erosion. Vendor dependence. #ATL280 === 19. Instagram === AI sounds confident. Your tax research still needs authoritative sources. #TaxResearch #ATL280 === 20. Instagram === Do not let AI turn your review process into a rubber stamp. #AccountingAI #ATL280 == Companies, organizations, products, and services mentioned == {| class="wikitable" ! Name !! Context !! X !! Facebook !! LinkedIn !! Instagram |- | AICPA || Framework context || Not verified || Not verified || Not verified || Not verified |- | Internal Revenue Service (IRS) || Tax authority and risk framework context || Not verified || Not verified || Not verified || Not verified |- | CPA Practice Advisor || Podcast presenter || Not verified || Not verified || Not verified || Not verified |- | The Tax Adviser || Article about the proposed framework || Not verified || Not verified || Not verified || Not verified |- | ChatGPT / OpenAI || Example of generative AI output risk || Not verified || Not verified || Not verified || Not verified |- | KPMG || Mention of simulation-style professional training || Not verified || Not verified || Not verified || Not verified |- | Tesla || Autonomous driving liability analogy || Not verified || Not verified || Not verified || Not verified |- | Wikipedia || AI source reliability discussion || Not verified || Not verified || Not verified || Not verified |- | TikTok || Tax advice analogy || Not verified || Not verified || Not verified || Not verified |} == Editorial and sourcing notes == * Based on the October 23, 2026 episode transcript and timestamped SRT. * Framework discussed as proposed; this page does not claim it is a binding IRS regulation. * Social media handles are intentionally not supplied without verification. * Timestamp labels are approximate segment start times. * No episode streaming URL or official slide deck URL was supplied.

Podcast

Bftcpa606 — Fri, 23 Oct 2026 12:48:23 GMT

Episode List (2025-Present, episodes 187-)

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	! Ep# !! Title !! CPAPA Link !! Record Date !! Publish Date		! Ep# !! Title !! CPAPA Link !! Record Date !! Publish Date
			\|-
			\|[https://cpate.ch/280 280]
			\|[[ATL280\|Proposed AICPA-IRS Tax AI Risk Framework]]
			\|atl280pub
			\|10/2/2026
			\|10/23/2026
	\|-		\|-
	\|[https://cpate.ch/279 279]		\|[https://cpate.ch/279 279]

ATL279

Bftcpa606 — Fri, 16 Oct 2026 14:12:59 GMT

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			[[File:ATL279.jpg\|thumb\|ATL279 - Tecnology Backlash - "Techlash"]]

	= ATL279: Tech Backlash =		= ATL279: Tech Backlash =

File:ATL279.jpg

Bftcpa606 — Fri, 16 Oct 2026 14:12:13 GMT

Bftcpa606 uploaded File:ATL279.jpg

New page

ATL279: Technology Backlash - "Techlash"

ATL279

Bftcpa606 — Fri, 16 Oct 2026 14:11:07 GMT

Show changes

ATL279

Bftcpa606 — Fri, 16 Oct 2026 14:10:46 GMT

Created page with "= ATL279: Tech Backlash = '''Episode:''' 279 '''Premiere:''' October 16, 2026 '''Recorded:''' September 11, 2026 '''Hosts:''' Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA '''Presented by:''' CPA Practice Advisor == Episode Summary == Technology companies have spent decades promising convenience, efficiency, and innovation. But what happens when consumers, communities, and regulators decide the costs are becoming too high? In this episode of Accounting Technolog..."

New page

= ATL279: Tech Backlash = '''Episode:''' 279 '''Premiere:''' October 16, 2026 '''Recorded:''' September 11, 2026 '''Hosts:''' Randy Johnston and Brian F. Tankersley, CPA.CITP, CGMA '''Presented by:''' CPA Practice Advisor == Episode Summary == Technology companies have spent decades promising convenience, efficiency, and innovation. But what happens when consumers, communities, and regulators decide the costs are becoming too high? In this episode of Accounting Technology Lab, Randy Johnston and Brian Tankersley examine the growing backlash against Big Tech, from multibillion-dollar legal settlements and privacy controversies to surveillance cameras and opposition to massive AI data centers. The discussion explores declining public confidence in technology companies, concerns about Flock license-plate recognition cameras, and the environmental and infrastructure challenges associated with hyperscale computing facilities. Electricity consumption, water usage, noise pollution, and local opposition are creating new obstacles for an industry accustomed to rapid expansion. For accounting professionals, these developments raise important questions about cloud computing, client confidentiality, vendor accountability, and regulatory compliance. Randy and Brian explain why trusting a familiar technology brand is no substitute for evaluating its security practices, contractual commitments, and data governance. They also offer practical recommendations for managing vendor relationships, including reviewing privacy policies, identifying subprocessors, examining access logs, and negotiating data portability and exit provisions. The central message: Technology remains essential to modern business, but responsible adoption requires greater transparency, stronger governance, and informed professional judgment. == Chapters == {| class="wikitable" ! Time !! Topic |- | 00:09 || Big Tech settlements and tech backlash |- | 02:14 || Amazon Prime and consumer protection |- | 03:34 || App stores and children's privacy |- | 04:54 || Flock cameras and surveillance |- | 06:05 || Declining confidence in technology companies |- | 09:49 || Surveillance governance failures |- | 13:43 || Opposition to AI data centers |- | 16:54 || Electricity, water and environmental costs |- | 18:45 || State privacy regulation |- | 20:28 || Grid capacity and hyperscale computing |- | 22:35 || Practical guidance for accounting firms |- | 26:30 || Vendor accountability |} == Quotable Moments == * '''06:05 — Brian Tankersley:''' "The public confidence in large tech companies is down at 20%." * '''09:49 — Brian Tankersley:''' "The legitimate technologies can create governance failures." * '''17:43 — Randy Johnston:''' "If you don't have water, it's a bad day." * '''22:35 — Brian Tankersley:''' "When you use cloud services, you want to make sure you own the data and you can get your data out." * '''22:35 — Brian Tankersley:''' "Transparency about subprocessors is non-negotiable." * '''26:30 — Randy Johnston:''' "We have to assume that many of these bigger, well-known vendors may not be doing all their job on governance." == Promotional Copy == '''Headline:''' Tech Backlash: When Innovation Outruns Trust '''Teaser:''' Big Tech faces lawsuits, communities are pushing back against AI data centers, and surveillance systems are raising uncomfortable questions. What does the growing tech backlash mean for accounting firms and their clients? == Social Media Posts == === 1. The techlash is here === Big Tech is facing growing scrutiny from consumers, regulators, and communities. From privacy settlements to AI data center opposition, the rules are changing. #ATL279 #AccountingTechnology === 2. Big Tech, little trust? === Public confidence in major technology companies has reportedly fallen to 20%. Should accounting firms rethink how they evaluate technology partners? #TechBacklash #CPA === 3. Your data. Their rules? === When your client data lives in the cloud, who can access it? Who audits that access? And can you get your data back? #DataGovernance #CloudSecurity === 4. The AI infrastructure reckoning === AI needs computing power. Computing power needs electricity, water, and land. Communities are questioning who pays the price. #AI #DataCenters === 5. Surveillance or security? === License-plate recognition cameras can help solve crimes, but access without proper controls creates serious privacy risks. #Privacy #Governance === 6. The hidden cost of convenience === A subscription you did not intend to purchase. An app-store fee you cannot avoid. A privacy policy you never read. #ConsumerProtection #BigTech === 7. The vendor exit test === Before you sign a new cloud agreement, ask: How do we get our data out if the relationship ends? #VendorRisk #AccountingFirms === 8. Trust, but verify === A familiar brand name is not proof of strong security controls. Ask for evidence, review the contract, and understand vendor responsibilities. #Cybersecurity #CPA === 9. What powers AI? === The AI revolution is about substations, cooling systems, water supplies, and communities living beside infrastructure. #AIInfrastructure #TechBacklash === 10. Who is watching the watchers? === Without access logs, oversight, and accountability, surveillance tools can be misused. #Privacy #InternalControls === 11. A state-by-state compliance puzzle === Privacy regulation is increasingly a state-level issue. Firms operating across state lines need a compliance roadmap. #Compliance #DataPrivacy === 12. Your cloud provider has providers === Do you know which subprocessors can handle your clients information? Revisit your vendor due diligence. #ThirdPartyRisk #Cloud === 13. AI versus the power grid === Can electricity infrastructure keep up with hyperscale AI development? Randy and Brian explore why this matters. #Energy #ArtificialIntelligence === 14. The accounting profession role === Accountants can help clients evaluate technology risk, contract provisions, regulatory exposure, and data ownership. #CAS #TrustedAdvisor === 15. Transparency is a control === Privacy policies, audit evidence, access logs, and identified subprocessors belong in serious vendor evaluations. #RiskManagement #AccountingTechnology === 16. The data center next door === Construction jobs and investment sound attractive. But what about noise, water consumption, and electricity rates? #DataCenters #Community === 17. Plan your exit before you enter === A technology contract is like a partnership agreement: exit provisions matter most when things stop going to plan. #CloudComputing #BusinessContinuity === 18. Technology is not the enemy === The problem is not innovation itself. It is innovation without sufficient accountability, transparency, and governance. #ResponsibleTech #AI === 19. Do not confuse compliance with trust === A checklist does not answer every question about data access, retention, privacy, and vendor behavior. #Governance #CyberRisk === 20. New episode: Tech Backlash === ATL279 premieres October 16! Big Tech settlements, surveillance, AI data centers, and vendor-risk lessons for accountants. #AccountingTechnologyLab #ATL279 == Companies and Services Mentioned == {| class="wikitable" ! Company or service !! X !! Facebook !! LinkedIn !! Instagram |- | Meta / Facebook || [https://x.com/Meta Meta] || [https://www.facebook.com/Meta Meta] || [https://www.linkedin.com/company/meta/ meta] || [https://www.instagram.com/meta/ meta] |- | Google || [https://x.com/Google Google] || [https://www.facebook.com/Google Google] || [https://www.linkedin.com/company/google/ google] || [https://www.instagram.com/google/ google] |- | Microsoft / Azure || [https://x.com/Microsoft Microsoft] || [https://www.facebook.com/Microsoft Microsoft] || [https://www.linkedin.com/company/microsoft/ microsoft] || [https://www.instagram.com/microsoft/ microsoft] |- | Amazon / Prime || [https://x.com/amazon amazon] || [https://www.facebook.com/Amazon Amazon] || [https://www.linkedin.com/company/amazon/ amazon] || [https://www.instagram.com/amazon/ amazon] |- | Apple / App Store || Not verified || [https://www.facebook.com/apple apple] || [https://www.linkedin.com/company/apple/ apple] || [https://www.instagram.com/apple/ apple] |- | TikTok || [https://x.com/tiktok_us tiktok_us] || [https://www.facebook.com/tiktok tiktok] || [https://www.linkedin.com/company/tiktok/ tiktok] || [https://www.instagram.com/tiktok/ tiktok] |- | Alibaba || [https://x.com/AlibabaGroup AlibabaGroup] || [https://www.facebook.com/Alibaba.com Alibaba.com] || [https://www.linkedin.com/company/alibaba-group/ alibaba-group] || [https://www.instagram.com/alibaba.com_official/ alibaba.com_official] |- | Zoho || [https://x.com/zoho zoho] || [https://www.facebook.com/zoho zoho] || [https://www.linkedin.com/company/zoho/ zoho] || [https://www.instagram.com/zoho/ zoho] |- | Flock Safety || Not verified || Not verified || [https://www.linkedin.com/company/flock-safety/ flock-safety] || Not verified |- | Kalshi || [https://x.com/Kalshi Kalshi] || Not verified || [https://www.linkedin.com/company/kalshi/ kalshi] || [https://www.instagram.com/kalshi/ kalshi] |- | 23andMe || [https://x.com/23andMe 23andMe] || [https://www.facebook.com/23andMe 23andMe] || [https://www.linkedin.com/company/23andme/ 23andme] || [https://www.instagram.com/23andme/ 23andme] |- | Tennessee Valley Authority || [https://x.com/TVAnews TVAnews] || [https://www.facebook.com/TVA TVA] || [https://www.linkedin.com/company/tennessee-valley-authority/ tennessee-valley-authority] || [https://www.instagram.com/tvanews/ tvanews] |} == Newsletter Copy == Big Tech is facing a growing backlash. In ATL279, Randy Johnston and Brian Tankersley discuss settlements, surveillance, AI data centers, and the practical governance questions accounting firms should ask about cloud providers. Premieres October 16, 2026. == Editorial Note == Figures and allegations discussed in the episode reflect the transcript and should be independently fact-checked before publication as established facts. Social accounts have not been individually verified.

Podcast

Bftcpa606 — Fri, 16 Oct 2026 14:09:58 GMT

Episode List (2025-Present, episodes 187-)

← Older revision		Revision as of 14:09, 16 October 2026
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			\|[[ATL279\|Tech Backlash]]
			\|atl279pub
			\|9/11/2026
			\|10/16/2026
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	\|[https://cpate.ch/278 278]		\|[https://cpate.ch/278 278]

ATL278

Bftcpa606 — Thu, 08 Oct 2026 23:05:08 GMT

Promotional Pull Quotes

Show changes

ATL278

Bftcpa606 — Thu, 08 Oct 2026 21:40:15 GMT

Created page with "thumb|ATL 278: Covered-ish: Microsoft, Google, OpenAI, Anthropic and the AI Liability Question"

New page

[[File:ATL278.jpg|thumb|ATL 278: Covered-ish: Microsoft, Google, OpenAI, Anthropic and the AI Liability Question]]

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Bftcpa606 — Thu, 08 Oct 2026 21:39:52 GMT

Bftcpa606 uploaded File:ATL278.jpg

New page

ATL278: Covered-ish: Microsoft, Google, OpenAI, Anthropic and the AI Liability Question

Podcast

Bftcpa606 — Thu, 08 Oct 2026 21:34:27 GMT

Episode List (2025-Present, episodes 187-)

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			\|[[ATL278\|Covered-ish: Microsoft, Google, OpenAI, Anthropic and the AI Liability Question]]
			\|[https://cpate.ch/atl276pub atl278pub]
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			\|10/09/2026
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	\|[[ATL276\|The Secrets Agents Keep (Guest: Alexis Kingsbury, Author]], [[ATL276\|"Accrual Intentions")]]		\|[[ATL276\|The Secrets Agents Keep (Guest: Alexis Kingsbury, Author]], [[ATL276\|"Accrual Intentions")]]
	\|[https://cpate.ch/~~atl226pub~~ atl276pub]		\|[https://cpate.ch/atl276pub atl276pub]
	\|9/18/2026		\|9/18/2026
	\|9/25/2026		\|9/25/2026

ATL277

Bftcpa606 — Wed, 30 Sep 2026 13:59:26 GMT

ATL277: Technology Mergers and Acquisitions

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Bftcpa606 — Wed, 30 Sep 2026 13:52:22 GMT

Bftcpa606 uploaded File:ATL277.jpg ATL277: Technology Mergers & Acquisitions

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== Summary ==
ATL277: Technology Mergers & Acquisitions

ATL277

Bftcpa606 — Wed, 30 Sep 2026 13:50:45 GMT

Created page with "= ATL277: Technology Mergers and Acquisitions = {{Podcast | number = ATL277 | title = Technology Mergers and Acquisitions | airdate = October 2, 2026 | recorded = September 11, 2026 | hosts = Randy Johnston; Brian F. Tankersley, CPA.CITP, CGMA | sponsor = CPA Practice Advisor }} == Episode Summary == The technology M&A market is sending some unusually clear signals about where the industry is headed. In ATL277, Randy Johnston and Brian Tankersley examine a wave of acq..."

New page

= ATL277: Technology Mergers and Acquisitions =

{{Podcast
| number = ATL277
| title = Technology Mergers and Acquisitions
| airdate = October 2, 2026
| recorded = September 11, 2026
| hosts = Randy Johnston; Brian F. Tankersley, CPA.CITP, CGMA
| sponsor = CPA Practice Advisor
}}

== Episode Summary ==

The technology M&A market is sending some unusually clear signals about where the industry is headed. In ATL277, Randy Johnston and Brian Tankersley examine a wave of acquisitions involving AI, semiconductors, data platforms, streaming, automation, and accounting technology—and what those deals may mean for accounting professionals.

The discussion ranges from Lattice Semiconductor's acquisition of AMI and onsemi's proposed Synaptics deal to Salesforce's acquisition of Fin, Progress Software's Domo transaction, Bending Spoons' Airtable acquisition, Sage's purchase of Bangert, NVIDIA's proposed acquisition of Hugging Face, and SpaceX's acquisition of Cursor. Stripe's agreement to acquire OpenRouter gets particular attention because AI routing could become an important layer of tomorrow's technology stack.

But the episode isn't really about dealmaking. It's about '''technology strategy and vendor risk'''. When a product your firm depends upon is acquired, its pricing, roadmap, integrations, support, privacy practices, or even its continued existence can change. Brian's advice: treat an acquisition as a trigger to revisit your contingency plan.

== Episode Highlights ==

* '''Technology consolidation is accelerating.''' M&A activity can help identify longer-term technology trends.
* '''AI infrastructure is becoming strategic.''' Stripe's OpenRouter agreement highlights the growing importance of model routing and token economics.
* '''AI agents are acquisition targets.''' Salesforce acquired Fin, formerly Intercom, for approximately $3.6 billion.
* '''Hardware and edge AI matter.''' Lattice acquired AMI, while onsemi agreed to acquire Synaptics.
* '''Data is increasingly valuable.''' The FOX/Roku transaction demonstrates the strategic importance of platforms, audiences, and first-party data.
* '''Accounting-adjacent M&A continues.''' Sage acquired longtime construction technology partner Bangert.
* '''Contingency planning matters.''' Firms should reassess their options whenever an important technology vendor changes ownership.

== Selected Quotes ==

{| class="wikitable"
! Time
! Speaker
! Quote
|-
| 05:34
| Brian Tankersley
| "I'm not sure how effective they are, though."
|-
| 08:32
| Brian Tankersley
| "There's a lot more to life than IQ points."
|-
| 12:04
| Brian Tankersley
| "There's a lot more data getting picked up than you may think."
|-
| 20:03
| Brian Tankersley
| "It's very expensive and difficult to switch."
|-
| 26:48
| Brian Tankersley
| "We live in interesting times, and stay tuned."
|-
| 26:48
| Brian Tankersley
| "You need to revise your contingency plans."
|-
| 26:48
| Brian Tankersley
| "You need to know that something big's changing, and you need to get ready."
|}

== Companies and Technologies Discussed ==

{| class="wikitable sortable"
! Company / Product
! Topic
|-
| AMI
| Platform firmware and infrastructure management
|-
| Lattice Semiconductor
| Acquisition of AMI
|-
| Cerebras Systems
| AI semiconductor technology
|-
| Intel
| Semiconductor technology
|-
| AMD
| Semiconductor and AI technology
|-
| NVIDIA
| AI hardware and proposed Hugging Face acquisition
|-
| Qualcomm
| Semiconductor and edge technology
|-
| Fin
| AI customer-service agents
|-
| Salesforce
| Acquisition of Fin
|-
| Slack
| Collaboration and agentic AI
|-
| Anthropic / Claude
| Frontier AI
|-
| OpenAI / ChatGPT
| Frontier AI
|-
| Google Gemini
| Frontier AI
|-
| Roku
| Streaming platform and first-party data
|-
| FOX Corporation
| Proposed Roku acquisition
|-
| Walmart
| Vizio owner
|-
| Vizio
| Smart TVs and SmartCast
|-
| TCL
| Smart televisions
|-
| Ubiquiti
| Network segmentation
|-
| Synaptics
| Edge and physical AI
|-
| onsemi
| Proposed Synaptics acquisition
|-
| Progress Software
| Acquisition of Domo's AI/data platform business
|-
| Domo
| BI, analytics, data integration and AI
|-
| ShareFile
| Progress-owned platform
|-
| Airtable
| Data, workflow and automation
|-
| Bending Spoons
| Airtable acquisition
|-
| Sage
| Bangert acquisition
|-
| Sage Intacct Construction
| Construction financial management
|-
| Bangert
| Construction technology and implementation
|-
| AskRichard
| AI-enabled onboarding
|-
| Stripe
| OpenRouter acquisition agreement
|-
| OpenRouter
| AI model gateway and routing
|-
| Hugging Face
| Models, datasets and AI applications
|-
| SpaceX
| Cursor acquisition
|-
| xAI / Grok
| AI platform
|-
| Anysphere / Cursor
| AI coding platform
|-
| GitHub
| Software and IPTV repository
|-
| VLC / VideoLAN
| Open-source media player
|}

== Key Takeaways for Accounting Firms ==

# Treat a vendor acquisition as a technology-risk event.
# Review contractual commitments, pricing protections, data ownership, and exit provisions.
# Determine whether integrations and APIs are likely to remain supported.
# Maintain current exports or backups of critical firm data where practical.
# Identify at least one realistic alternative for mission-critical systems.
# Watch for changes in privacy policies, telemetry, security practices, and AI data usage.
# Reevaluate vendor concentration and switching costs.
# Update the firm's technology contingency plan when ownership materially changes.

== Social Media Posts ==

# '''Your software vendor just got acquired. Now what?''' ATL277 looks beyond the M&A headlines to pricing, roadmaps, integrations, security, and contingency planning. #AccountingTechnology #CPA
# What can technology M&A tell us about the future? AI routers. Agents. Edge AI. Data platforms. Coding tools. First-party data. Follow the money in ATL277.
# Stripe + OpenRouter points toward a future where AI routing becomes part of the technology stack.
# Salesforce + Fin. NVIDIA + Hugging Face. SpaceX + Cursor. Stripe + OpenRouter. These are strategic bets on where AI goes next.
# '''"We live in interesting times, and stay tuned."''' ATL277 examines today's technology acquisition boom.
# An acquisition isn't just a Wall Street story when your accounting firm runs on the product being acquired.
# What's your plan when a mission-critical software vendor gets acquired? ATL277 makes the case for adding vendor ownership changes to your technology-risk playbook.
# AI agents may know the answer. That doesn't necessarily mean they know how to work with a client.
# Knowledge isn't the whole equation. Relationships, communication, judgment, and interpersonal skills still matter.
# Your television isn't necessarily just a television anymore. ATL277 looks at smart devices, first-party data, and IoT security.
# Practical security lesson: keep IoT devices away from systems containing sensitive client data.
# M&A can reveal strategy before the marketing department does.
# Sage + Bangert demonstrates that implementation expertise and IP can have strategic value.
# Airtable's role in workflow, automation, data, and AI orchestration helps explain its strategic value.
# Useful AI requires more than a model. It needs data, context, governance, integration, and control.
# NVIDIA + Hugging Face illustrates why models, datasets, applications, developers, and ecosystems matter alongside chips.
# Software consolidation can make a product physically—or financially—unavailable.
# Every accounting firm's technology inventory should answer: '''"What would we do if this product disappeared?"'''
# Don't watch technology M&A only as an investor. Watch it as a customer.
# '''ATL277: Technology Mergers and Acquisitions''' — Follow the money through AI, hardware, automation, data platforms, and accounting technology.

== Hashtags ==

#AccountingTechnologyLab #AccountingTechnology #AccountingTech #CPA #ArtificialIntelligence #AI #MergersAndAcquisitions #AgenticAI #AIRouters #TechnologyStrategy #VendorManagement #RiskManagement #Cybersecurity #SaaS #AccountingInnovation #TechnologyGovernance

== Practical Takeaway ==

Technology acquisitions aren't merely financial events for accounting firms. They are potential changes to the firm's technology risk profile. When a mission-critical vendor is acquired, firms should revisit pricing assumptions, integrations, data portability, security, contractual protections, and alternative products before changes force the issue.

Podcast

Bftcpa606 — Wed, 30 Sep 2026 13:49:56 GMT

Episode List (2025-Present, episodes 187-)

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			\|[[ATL277\|Technology Mergers and Acquisitions, September 2026]]
			\|[https://cpate.ch/atl277pub atl277pub]
			\|9/11/2026
			\|10/2/2026
	\|-		\|-
	\|[https://cpate.ch/276 276]		\|[https://cpate.ch/276 276]