Dunstan Allison-Hope writes about how companies can report on sustainability and responsible AI, with a focus on human rights, material impacts, and putting reporting standards into practice.
Dunstan Allison-Hope writes about sustainability reporting, business and human rights, and responsible AI.
Their posts focus on how reporting rules work in practice: what companies should disclose, whose impacts might be missed, and how human-rights due diligence can inform assessments.
Follow their work for close readings of technical standards that connect their details to accountability for people and communities.
A distinctive feature of Dunstan Allison-Hope’s writing is how it pairs a rule’s stated purpose with the practical consequences of its wording or application.
In discussing revised ESRS drafts, they welcome clearer structure but also flag how removing “for example” from human-rights disclosures could affect interpretation.
In a post about technology companies’ reporting, they contrast the share treating affected communities as a material topic with the much higher share reporting climate change, then ask whether a focus on customers overlooks other people affected by technology.
They do not call for simpler rules across the board: they value the EU AI Act while questioning whether its impact-assessment requirement reaches enough cases, and argue that core human-rights diligence should accompany detailed requirements.
Together, these examples make the work useful to readers trying to understand not just what a standard says, but what its structure may leave out.
Across five LinkedIn posts, Dunstan Allison-Hope argues for reporting that starts with real effects on people, not just checklist compliance.
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The posts connect human-rights due diligence to materiality assessments, call for responsible AI to be covered by existing reporting standards, and question whether detailed rules reach the people and impacts they are meant to protect.
Start with the impacts, not the checklist
Allison-Hope argues that standards cannot cover every important issue for every company.
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Without sector-specific standards, companies need to identify the material impacts, risks and opportunities specific to their business, rather than treating general standards as a complete checklist.
After EFRAG dropped plans for sector-specific ESRS, Allison-Hope argued that entity-specific disclosures matter more. The post calls for genuine analysis and says informal guidance from credible, multi-stakeholder groups can help fill gaps left by formal standards.
A materiality assessment should draw on due diligence, not stand apart from it.
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Allison-Hope regrets the removal of an explicit ESRS sentence linking assessments of negative impacts to the UN Guiding Principles on Business and Human Rights and OECD Guidelines, but notes that revised ESRS 1 still connects sustainability due diligence with materiality.
In reviewing the ESRS exposure drafts, Allison-Hope points to paragraphs 27, 54 and 56 of revised ESRS 1, which retain that connection even though the earlier sentence they often quoted is gone.
Allison-Hope argues that companies need better guidance for reporting AI-related impacts through existing financial and sustainability standards, rather than another standalone reporting standard.
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Reporting alone is not enough; investors and other stakeholders also need useful information to make decisions.
A post about Partnership on AI's draft Disclosure Recommendations says AI governance, strategy, impacts, risks and opportunities matter across industries such as finance, healthcare and retail—not just for prominent AI companies. It invites companies, investors and other stakeholders to test the recommendations.
Look beyond customers when assessing technology's effects
Technology can affect communities and public life, not just customers and end users.
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Allison-Hope warns that focusing on consumer impacts may overlook effects on people who are not users, especially when technology affects wider systems or is used in a business-to-business context.
Allison-Hope contrasts a reported 17% of tech companies identifying ESRS S3, affected communities, as material with 94% identifying climate change. The post notes that S3 includes civil and political rights and suggests several possible reasons for the gap, including a stronger focus on consumer impacts under S4.
Judge regulation by whether it advances accountability
Allison-Hope wants regulation to protect human rights, but questions whether complexity helps achieve that goal.
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The post supports the EU AI Act while asking whether greater emphasis on due diligence and transparency could extend meaningful protection more broadly.
After reading the AI Act, Allison-Hope notes that its Article 27 fundamental-rights assessment applies only in a narrow set of cases. The post argues that the CSDDD may be more relevant to human-rights due diligence for many companies deploying AI, and advises starting with the UN Guiding Principles, OECD Guidelines and relevant AI guidance before tackling more complex requirements.
What actually changed in the EFRAG ESRS exposure drafts, and which details matter to companies and auditors?
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This post maps the revisions beyond the headlines.
Dunstan Allison-Hope calls the revisions a significant improvement and highlights four changes.
The overall purpose is clearer, and the details better match the big picture.
The structure is more logical: material impacts, risks, and opportunities have moved out of the strategy section, while policies and actions have moved out of impacts, risks, and opportunities.
Revised ESRS S3 and S4 drop the term 'for example' from human rights lists, which could change how auditors read the scope of civil and political rights.
The old sentence tying the materiality of negative impacts to the UNGPs and OECD Guidelines is gone.
But paragraphs 27 and 56 of revised ESRS 1 say sustainability due diligence should inform the materiality assessment, and paragraph 54 references the UNGPs and OECD in its definition of sustainability due diligence.
For brands planning a campaign
For an advisory firm, this post offers a ready-made spine for a webinar or white paper: walk through the four changes, show how due diligence informs materiality, and flag the auditor risk created by removing 'for example' from S3 and S4.
Why can a widely adopted reporting standard still miss systemic technology impacts?
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This post explains the gap between standard text and company practice.
Dunstan Allison-Hope contrasts a discussion of technology's effects on democracy, human rights, and freedom with an EFRAG State of Play 2025 report on ESRS implementation.
One table shows that just 17% of tech companies treat ESRS S3 on affected communities as material, compared with 94% for climate change.
The post notes that ESRS S3 references communities' civil and political rights and lists freedom of expression, freedom of assembly, and impacts on human rights defenders as examples.
They suggest the low figure reflects several factors: sustainability teams oriented toward environmental impacts, ESRS difficulties with downstream impacts, and many large tech companies not yet reporting.
The biggest factor may be a focus on ESRS S4 on consumers and end users, even though not everyone affected by technology is a user or customer.
For brands planning a campaign
This post could anchor a white paper section on S3 versus S4 and responsible AI. A consulting firm could propose a diagnostic for technology clients to test whether they are missing affected communities and systemic impacts.
This post makes the case for integrating AI governance into existing financial and sustainability reporting instead of creating another standalone standard.
Dunstan Allison-Hope argues that companies do not need a new responsible AI reporting standard; they need guidance on integrating responsible AI into existing sustainability reporting standards.
The post notes investor interest in the IPOs of OpenAI, Anthropic, and SpaceX, but says AI governance, strategy, impacts, risks, and opportunities are material for companies in finance, healthcare, retail, and other industries.
That information belongs in formal financial and sustainability reports.
Existing venues include SEC filings, the ESRS, ISSB, and GRI, but the quality of current disclosures falls short.
The post introduces Partnership on AI's draft Disclosure Recommendations as a way to fill the gap and invites companies, investors, and other stakeholders to test them.
For brands planning a campaign
This post could anchor a webinar or white paper on integrating responsible AI into ESRS, ISSB, GRI, and SEC reporting. The Partnership on AI draft recommendations give clients a concrete opportunity to test their approach.
What fills the gap when sector-specific ESRS standards are removed?
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This post explains entity-specific disclosures and the culture change behind double materiality.
Dunstan Allison-Hope asks whether removing sector-specific standards from the ESRS increases the importance of entity-specific material disclosures: material impacts, risks, or opportunities not covered by an ESRS but still disclosed because of their significance.
Since many material topics are company- or sector-specific and EFRAG will no longer develop sector-specific standards, companies must follow the spirit of double materiality rather than treat the ESRS as a checklist.
The post describes the exposure-draft text on entity-specific material disclosures, including ESRS 1 paragraphs 10 and 11, as quite good, but says there has been little commentary on the shift.
Success will require a culture shift toward authentic analysis in materiality assessments, alongside informal sector-specific and issue-specific recommendations from multi-stakeholder organizations.
For brands planning a campaign
For an advisory firm, this post supports a service around redesigning materiality assessments. A white paper could map informal sector and issue recommendations and explain the shift from checklist compliance to authentic, entity-specific analysis.
How does the EU AI Act's fundamental rights impact assessment apply, and why might CSDDD matter more for AI at many companies?
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This post shows the gap between a law's reputation and its practical scope.
Dunstan Allison-Hope asks whether simplicity supports accountability in business and human rights more than complexity.
After reading more than 140 pages of the EU AI Act, they note that Article 27's requirement to undertake a fundamental rights impact assessment applies only to a narrow set of scenarios: seven of the eight high-risk AI systems designated by the European Commission, and only when deployers are public bodies or private entities providing public services.
The post argues that the non-AI-specific Corporate Sustainability Due Diligence Directive may be more relevant than the AI Act for human rights due diligence at many companies deploying AI.
It still values the AI Act's requirements on quality, transparency, accuracy, and human oversight, and wants the Act to succeed.
Removing complexity for the few, the post suggests, could create room to emphasize fundamentals for the many.
Companies should start with the UNGPs, OECD Guidelines, and relevant AI principles before moving to more complex requirements.
For brands planning a campaign
This post could anchor a webinar on integrating UNGPs into sustainability reporting and AI governance. Compare Article 27's scope with CSDDD and propose human rights assessments for AI systems beyond the narrow high-risk set.
Human rights materiality depends on due diligence, not just impact severity2
Close reading of the revised EFRAG ESRS exposure drafts1
The ESRS S3 blind spot in technology companies1
Entity-specific disclosures when sector standards are dropped1
Responsible AI disclosure belongs inside existing standards1
Simplicity versus complexity in regulation, argued through outcomes1
Close reading of the revised EFRAG ESRS exposure drafts
Dunstan Allison-Hope reviewed the EFRAG European Sustainability Reporting Standards exposure drafts and judged the revisions a significant improvement, setting out four changes.
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The standards’ overall purpose is reinforced.
Their structure is clearer: material impacts, risks, and opportunities now sit in the IRO section rather than strategy, while policies and actions sit in metrics and targets rather than IRO.
The phrase “for example” was dropped from human rights language in revised ESRS S3 and S4, a detail they flag as having real audit consequences given the wide range of civil and political rights in scope.
And although the sentence linking the materiality assessment of a negative impact to the UNGPs and OECD Guidelines has been removed, paragraphs 27, 54, and 56 of revised ESRS 1 still require sustainability due diligence to inform materiality.
The post also notes the practical cost of structural change: unpicking work already completed.
Starts with the big picture of a standard, then checks the details and numbers each observation so it can be verified against the draft text.
For brands planning a campaign
A consulting firm can build a webinar or white paper session around four points: what changed, what wording matters for human rights disclosure, and where ESRS 1 now links due diligence and materiality. The auditor-interpretation warning about “for example” gives clients a concrete talking point.
Human rights materiality depends on due diligence, not just impact severity
Across the ESRS posts, the recurring argument is that a company’s materiality assessment of negative human rights impacts should be informed by the due diligence process defined in the UNGPs and the OECD Guidelines.
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Allison-Hope previously quoted the ESRS sentence that said this directly and regrets its removal from the exposure drafts.
They point out that revised ESRS 1 paragraphs 27, 54, and 56 preserve the substance by tying sustainability due diligence to the materiality assessment.
They treat this as the bridge between materiality and salience in human rights disclosures.
For brands planning a campaign
This makes the case for a white paper on integrating UNGPs into sustainability reporting: the standards still expect due diligence to shape what gets reported, even though the explicit sentence was cut. The practical method for clients is to feed the materiality assessment with a due diligence process.
Comparing an EFRAG State of Play 2025 table with a discussion about tech and democracy, Allison-Hope notes that only 17% of tech companies conclude that ESRS S3, affected communities, is material, compared with 94% for climate change.
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Yet ESRS S3 explicitly covers impacts on communities’ civil and political rights, including freedom of expression, freedom of assembly, and impacts on human rights defenders.
They suggest possible causes: sustainability teams focused on environmental impacts, the standards’ difficulty with downstream impacts, many large tech companies not yet reporting, and over-reliance on ESRS S4, which covers consumers and end users.
The core point is that people affected by technology are not only users or customers; in a B2B context, this gap is especially easy to miss.
Sets a reporting statistic alongside a live public debate to show what the number obscures, then distinguishes possible explanations rather than asserting one.
For brands planning a campaign
A strong angle for a consulting firm advising tech clients: the distinction between S3 and S4, and why a company that treats consumers as the only affected group is likely under-reporting. A white paper or webinar could use this as a worked example of choosing the right standard for an impact.
Entity-specific disclosures when sector standards are dropped
With sector-specific ESRS removed, Allison-Hope argues that entity-specific material disclosures matter more because many material topics are specific to a company or sector and were never covered by standards written for all industries.
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The risk is that companies treat ESRS as a checklist instead of applying the spirit of double materiality: identifying material impacts, risks, and opportunities.
They praise the entity-specific text in the exposure drafts, including ESRS 1 paragraphs 10 and 11, and call for a shift toward authentic analysis in double materiality assessments.
Informal sector and issue disclosure recommendations from multi-stakeholder organizations can help, even if they fall short of formal standards.
They note that this approach assumes companies stay on a path of increased disclosure despite pressure to reverse course, and argue that technical work should stand the test of time.
This post addresses people following ESRS revisions while making the implications of technical changes accessible to a wider audience.
For brands planning a campaign
Useful for a consulting offer that helps clients build entity-specific disclosures after the loss of sector standards, and for positioning a firm’s informal sector guidance as filling that gap.
Responsible AI disclosure belongs inside existing standards
Allison-Hope argues that companies do not need a new responsible AI reporting standard; they need guidance on integrating responsible AI into the sustainability reporting standards they already use.
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Interest in what OpenAI, Anthropic, and SpaceX disclose to investors about AI impacts, risks, and opportunities is real, but AI governance and strategy information is material across finance, healthcare, retail, and other industries, and belongs in formal financial and sustainability reports.
The existing instruments are SEC filings for financially material information, ESRS for impacts on people and the environment, and the voluntary ISSB and GRI standards.
The post announces Partnership on AI draft Disclosure Recommendations, published to address the gap, notes that current disclosure quality falls short, and invites companies, investors, and other stakeholders to test the draft.
For brands planning a campaign
Direct support for a white paper on disclosure quality: the argument that AI reporting is an integration problem, not a new-standard problem, with Partnership on AI’s draft recommendations as a testing ground clients could join.
Simplicity versus complexity in regulation, argued through outcomes
Re-reading the EU AI Act, Allison-Hope finds that the fundamental rights impact assessment in Article 27 applies only to a narrow set of scenarios: seven of the eight high-risk AI system categories designated by the European Commission, and only when deployers are bodies governed by public law or private entities providing public services.
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They argue that the non-AI-specific CSDDD may be more relevant to human rights due diligence at many companies deploying AI than the AI Act.
They want the AI Act to succeed, but ask whether dialing back detailed specifications while reinvigorating the core of diligence and transparency around impacts on people is a better defense when the Act comes under attack, and whether simplifying ESRS can increase rather than decrease impact.
Their advice to companies deploying AI is to start with the UNGPs, OECD Guidelines, and relevant AI principles, then move to more complex requirements.
They frame the question—what kind of regulation actually produces the desired changes?—to head off criticism that they sound like a corporate shill.
For brands planning a campaign
Gives a consulting firm a defensible line on regulation: assess AI against the fundamentals first, then the detailed regime. It also suits a webinar segment on where CSDDD and the AI Act overlap for companies deploying AI.
Each opens with a plain question or direct statement of the argument, then moves through numbered or clearly separated points.
Technical material is explained for readers who do not work inside the standards, with practical consequences made clear, such as how auditors might read a wording change or what a company should do differently.
Allison-Hope qualifies their position where it matters—for example, noting that advocating simplicity is not a corporate position but a view about which rules produce results—and uses light self-deprecation about nerding out over standards.
Big picture before detail; a question or claim up front; evidence tied to specific clauses, tables, and named instruments; exceptions and uncertainties stated rather than smoothed over.
For brands planning a campaign
For a firm commissioning content, this approach translates well to a webinar or white paper: lead with the reader’s decision, show the clause or statistic that drives it, and state the practical action. It also offers an editing standard for content written under the creator’s name.
The posts show Dunstan Allison-Hope analyzing EFRAG sustainability reporting standards and working with Partnership on AI on responsible AI disclosure recommendations.
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No employer, sponsor, affiliate, owned business, investment, or client relationships are stated in the posts.
EFRAG
Mention
Dunstan Allison-Hope repeatedly analyzes EFRAG's European Sustainability Reporting Standards, including the exposure drafts and the 2025 State of Play report.
Dunstan Allison-Hope's posts track revisions to European sustainability reporting standards and how human-rights due diligence and responsible AI fit into disclosure.
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Start with their close reading of the EFRAG ESRS exposure drafts, which sets out four changes and locates the due diligence link to materiality in revised ESRS 1.
Their post on technology and ESRS S3 tests a reported statistic against the standard's actual scope.
The responsible AI post explains why AI governance belongs inside existing reporting rather than in a new standard.
The EU AI Act post offers the clearest example of their wider argument about complexity, simplicity and whether rules reach the impacts they are meant to protect.
European Sustainability Reporting Standards (ESRS)Corporate Sustainability Reporting Directive (CSRD)Double materialityHuman-rights due diligenceBusiness and human rightsResponsible AI disclosureEU AI ActEntity-specific disclosuresAffected communities in technologySustainability standards analysisHuman rights and AI policyRegulatory close readingPlain-language explainerLinkedIn postsSustainability reporting teamsHuman-rights practitionersAI governance teamsInvestors and disclosure users
Giovanna Jagger
Jagger writes from the revised ESRS moment, translating the framework into practical questions for business leaders: what they measure, what evidence they have and where action is falling short.
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Both treat reporting as a prompt for better decisions rather than a publishing exercise.
Jagger's posts focus on corporate real estate, workplace strategy and healthy buildings, and describe a consulting approach to aligning strategy and action. Allison-Hope focuses more on standards interpretation, human-rights due diligence and responsible AI disclosure.
Hesse also analyses the direction of ESRS, ISSB and SASB and asks what ESG information is actually useful for decisions.
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Both compare reporting frameworks and distinguish useful signals from reporting volume.
Hesse writes from an investor and data-provider perspective, focusing on financially material, industry-specific KPIs, long time series and portfolio applications. Allison-Hope takes a human-rights and standards-interpretation perspective, with affected communities and AI disclosure as recurring concerns.
Tull also explains CSRD and ESRS requirements for practitioners, including double materiality, value-chain visibility and governance.
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Both make technical reporting obligations concrete for the teams responsible for acting on them.
Tull's posts focus on procurement and supply chains, including supplier codes, risk analysis and advisory subscription packages. Allison-Hope's focus is standards text, human-rights due diligence and responsible AI, with less emphasis on procurement services.
Dunstan Allison-Hope’s LinkedIn posts may suit a campaign for sustainability and human-rights professionals working on ESRS, corporate reporting or responsible AI.
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They include a close reading of revised ESRS drafts and an argument for using existing reporting standards to disclose AI-related impacts. For a campaign targeting professional audiences, ask for documented audience survey results or another source showing followers’ roles and seniority.
Dunstan Allison-Hope's five posts cover ESRS, CSRD, the EU AI Act and responsible AI disclosure, but describe no partnership, sponsorship or paid-collaboration formats.
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They state no rate card, sponsored-post format, speaking arrangement, advisory package or booking process.
The closest example of a working relationship is a collaboration with Partnership on AI on draft AI Disclosure Recommendations: they write about working with named colleagues and invite companies, investors and other stakeholders to test the drafts.
This is a collaborative work product, not a sponsorship offer; the posts give no commercial terms, deliverables or contact route.
Buyers should not plan a sponsored-content or paid-placement campaign on the basis of these posts.
Before pursuing product promotion or a paid speaking engagement, ask Allison-Hope to confirm availability, commercial terms and deliverables.
A sustainability consulting firm wants to advise clients on ESRS and responsible AI disclosure, and wants a webinar or white paper on integrating the UNGPs into sustainability reporting.
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Reasons
The firm needs someone who turns standard text into client decisions. The ESRS post names four changes, separates those that matter for practice from cosmetic revisions, and flags a specific audit consequence: dropping the words "for example" from the human rights lists in revised ESRS S3 and S4 narrows how auditors may read the scope of civil and political rights. That gives clients a talking point, not just a summary of headlines.
The white paper thesis is already in the material: companies do not need a new responsible AI reporting standard; they need guidance on integrating responsible AI into the standards they use. The post names ESRS, ISSB, GRI, and SEC filings as places for AI governance, strategy, impacts, risks, and opportunities, and points to draft disclosure recommendations that companies and investors can test.
The UNGP integration angle is documented. The sentence tying the materiality assessment of a negative impact to the UNGPs and OECD Guidelines is gone from the exposure drafts, but paragraphs 27, 54, and 56 of revised ESRS 1 keep sustainability due diligence feeding the materiality assessment. A webinar can walk through that bridge step by step, including the parts the post's author regrets losing.
A second segment comes from the EU AI Act post: the fundamental rights impact assessment in Article 27 applies to seven of eight high-risk system categories designated by the European Commission, and only where deployers are public bodies or private entities providing public services. The argument that the non-AI-specific CSDDD may matter more for human rights due diligence at many companies deploying AI gives the firm a defensible position on regulation.
The writing method suits the format. Each post opens with the reader's decision, moves through numbered or separated points, cites specific clauses and tables, and states what a company should do differently—the structure a client webinar or paper needs.
The author also describes working with Partnership on AI on draft disclosure recommendations and invites companies, investors, and other stakeholders to test them, giving the firm a ready call to action.
Limits
The fit rests on analytical commentary about standards, policy, and disclosure practice. The posts do not document training delivery, client case studies, or advisory engagements; ask for relevant examples before booking.
The audience section records topic relevance but no measured follower roles or seniority. Ask for audience survey data or another source before promising registrations from a particular job function.
Verdict
Strong fit for an advisory content brief.
When to choose a specialist
An AI governance software vendor wants a paid LinkedIn sponsored-post series with a product demo call to action, or a paid keynote at its customer summit with lead-generation follow-up.
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Reasons
None of the five posts mentions sponsorships, paid speaking, or paid collaborations. They provide no rate card, deliverable list, booking process, or commercial inquiry route.
The posts cover standards, regulation, and disclosure practice; none endorses a product, promotes a vendor, or calls for a purchase. The described collaboration with Partnership on AI is a joint work product on draft disclosure recommendations. The author writes about working with named colleagues and invites testing, making it a collaborative output rather than a paid placement.
The audience section shows subject-matter relevance, not follower demographics. The posts cannot guarantee a defined set of compliance or procurement buyers.
The posts here do not document commercial offers; this does not mean Dunstan Allison-Hope never accepts sponsorships or paid work. A vendor brief of this kind would need a confirmed commercial agreement, which the posts here do not provide.
The posts provide no evidence of past paid speaking, audience testimonials, or lead-generation results. Ask for these before booking a keynote.
Limits
A related gap: Dunstan Allison-Hope's posts here do not cover signature work such as books, shows, or career changes that a general reader searching this name may expect to find. Clarify this before any release decision, because a reader who knows of a book or programme not covered here would find the profile incomplete.
Verdict
Not supported by the posts.
A worked campaign example
Evidence gaps
Before committing, confirm that the positions still reflect current drafts and agree on any co-presenter or review process. The posts do not establish whether the author delivers training or advisory sessions, so confirm delivery and terms separately.
Format
A 45-minute client webinar with a companion white paper. The webinar carries the argument; the paper preserves the clause-level detail and worked diagnostic so readers can act without the recording.
Spine
Lead with the client's decision: which standards and disclosures apply to AI and human rights, and where due diligence fits.
Walk through the four ESRS changes: the reinforced overall purpose; the moved blocks on impacts, risks, and opportunities, and on policies and actions; the removal of "for example" from the human rights lists in S3 and S4; and the lost sentence tying negative-impact materiality to the UNGPs and OECD Guidelines.
Show where the due diligence link now sits: paragraphs 27, 54, and 56 of revised ESRS 1 tie sustainability due diligence to the materiality assessment, while paragraph 54 defines sustainability due diligence by reference to the UNGPs and OECD Guidelines. Close with the audit risk created by the wording change, which makes the point urgent for the client.
Work through one determination: a technology company deciding whether affected communities are material. Use the reported figure that 17% of tech companies treat ESRS S3 as material, against 94% for climate change, and explain why relying on ESRS S4 alone understates impacts. People affected by technology are not only users or customers; impacts also run through systems, a point that can be easy to miss in a B2B setting.
Turn to responsible AI disclosure: make the case for integrating AI governance and impacts into ESRS, ISSB, GRI, and SEC reporting rather than creating a new standard, using the draft disclosure recommendations as a testing ground clients can join.
Close with the regulatory scope question: Article 27 of the EU AI Act covers seven of eight high-risk categories and applies only to public bodies or private entities providing public services. For human rights due diligence at many companies deploying AI, the CSDDD may be more relevant. Start with the UNGPs, OECD Guidelines and relevant AI principles, then move on to the more complex requirements.
End with three client next steps: review whether the last materiality assessment used due diligence output, test the affected-communities determination against the S3 scope, and decide whether to join the draft disclosure testing.
Title
Due diligence is the bridge: integrating the UNGPs into ESRS and responsible AI disclosure
Who it is for
Sustainability and reporting leads at companies that already report under ESRS or expect to, plus legal and human rights teams at companies deploying AI.
Why it works
The webinar and paper share one argument, with the affected-communities determination as a concrete case for the audience to follow. The firm can build both around the same spine rather than making two separate arguments.
Worked angle
The argument is that simplification and ambition are not opposites. Dialling back detailed specifications while reinvigorating diligence and transparency around impacts on people is a better way to protect the rules that matter. The same argument applies to ESRS simplification and the AI Act, allowing the firm to position its offer as compliance that can withstand changes to the standards, not compliance with just one version.
A better choice when the firm's clients work in corporate real estate, facilities, or workplace teams, or when the reporting problem is scattered evidence rather than standard wording.
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Jagger's posts ask workplace and real estate leaders which ESG priorities their buildings can influence, what evidence they already collect across the portfolio, and where ownership, measurement, or action is missing.
The revised ESRS serves as the trigger for that conversation.
If the firm wants a concrete operational entry point into ESRS for a property-heavy client base, this is closer to the task than a clause-by-clause standards reading.
The material stays inside buildings and workplace strategy.
It does not address responsible AI disclosure or the link between the UNGPs and the materiality assessment, both central to the firm's brief.
A webinar built on Jagger would need a different thesis and audience.
Where Dunstan Allison-Hope reads standard text and draws out audit consequences, Jagger turns existing initiatives into a reporting narrative: the firm gains an implementation angle but loses the human rights and AI argument.
A better choice when the client decision is which ESG data matters for investment decisions and the audience is asset owners, asset managers, or index providers.
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Hesse argues that ESG data becomes useful when it is financially material, industry-specific, globally comparable, and decision-useful for risk, valuation, and capital allocation.
Hesse points to the SD-KPI Standards, a long ESG history, and overlap with SASB/ISSB.
If the firm's offer targets investor-facing clients weighing ESRS against ISSB, this is the closer match on materiality.
The frame is financial materiality and portfolio analytics, not human rights due diligence or responsible AI.
There is no UNGP thread or treatment of disclosure quality for AI impacts; the argument is that a small set of sector-specific, financially material KPIs signals more than broad reporting.
A webinar or white paper with Hesse would address which data to trust and how it feeds capital allocation—a different client question from human rights due diligence or responsible AI.
The posts promote a data product with a test-access link, so negotiate separately for a neutral standards analysis.
A better choice when the firm wants a productized offer it can put in front of clients immediately.
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Tull packages sustainable procurement and CSRD support into subscription tiers with named deliverables and a discount deadline.
Its posts cover procurement's role in value-chain transparency, supplier codes of conduct, and risk analysis across supplier tiers.
If the goal is to sell a defined CSRD and supply-chain engagement rather than publish an argument, this is the service template the firm is looking for.
The posts market Tull Advisory & Consulting's own packages and center on procurement and supply chains.
They do not cover responsible AI or the UNGP-to-materiality link, and their claims describe package contents rather than independently analyze the standards.
The firm would be presenting a competing or complementary offer, not a neutral expert.
Choosing Tull shifts the deliverable from a thought-leadership webinar and paper to a packaged service—a different campaign decision.
Five LinkedIn posts by Dunstan Allison-Hope cover ESRS revisions and implementation, human-rights due diligence, affected communities and responsible AI disclosure.
The posts have no publication dates, so they do not show how the themes have changed over time or represent a complete career or posting history.
