Letter to Kalbir Sohi. - The UK’s Chief AI Officer
Dear Mr Sohi,
THE INTELLIGENT TRANSFORMATION OF GOVERNMENT
I am writing on behalf of X from GENERAL INTELLIGENCE PLC to introduce a substantial portfolio of British intellectual property relating to intelligence and artificial intelligence, together with thirty associated consultancy frameworks developed by the company.
Your appointment as the Government's first Chief Artificial Intelligence Officer represents an important development in the practical application of artificial intelligence across the public sector. The responsibility for identifying, evaluating and scaling artificial intelligence applications across government raises questions that extend well beyond technology itself. They concern the quality of public services, institutional capability, operational effectiveness, public trust, the use of information and the ability of government to make better decisions.
These are precisely the wider questions that underpin our work.
I believe that the intellectual property and consultancy frameworks developed by GENERAL INTELLIGENCE PLC may be of interest to you because they address the application of intelligence across organisations, industries and institutions, rather than treating artificial intelligence simply as a collection of technological products.
Our work is founded upon a straightforward proposition: Artificial intelligence is a means, not an end.
The objective should be to make organisations more intelligent: better able to understand their circumstances, make sound decisions, deliver their responsibilities, learn from experience and create lasting value.
For government, that objective has a particularly important dimension. The ultimate measure of technological progress should be its contribution to the effectiveness of the state and the lives of the people it serves.
1. GENERAL INTELLIGENCE PLC — A BRITISH INTELLECTUAL-PROPERTY PORTFOLIO
GENERAL INTELLIGENCE PLC is a Scottish company established in 1896.
X is the company's trading name and registered trade mark. Over time, the company has developed an extensive body of intellectual property concerned with intelligence, artificial intelligence, general intelligence, superintelligence and related fields.
The company describes its intellectual-property portfolio as comprising thirty UK trade marks in Class 42, together with more than one hundred additional intelligence-related intellectual-property assets.
Among the principal names within the portfolio are:
- INTELLIGENCE®
- GENERAL INTELLIGENCE®
- SUPERINTELLIGENCE®
- UNIVERSAL INTELLIGENCE®
The portfolio is supported by an extensive body of written material. The company's website, contains more than 700 pages examining intelligence in human and artificial forms, including the strategic, technological, commercial and institutional implications of its development.
This is not simply a collection of trade marks. It represents a sustained intellectual and commercial undertaking concerned with the meaning, development and application of intelligence across different environments.
We believe that British-developed intellectual property of this nature deserves to be understood, developed and put to constructive use.
2. FROM ARTIFICIAL INTELLIGENCE TO INTELLIGENT GOVERNMENT
The introduction of artificial intelligence into government presents an opportunity to reconsider how public services are designed, delivered and improved.
However, the successful adoption of technology depends upon the quality of the organisation into which it is introduced.
A department may acquire an advanced artificial intelligence system without necessarily improving its ability to deliver a public service. It may automate an inefficient process, accelerate the handling of information without improving the resulting decisions, or introduce new dependencies without adequately understanding their implications.
Conversely, a carefully selected application, integrated into a well-designed service and supported by appropriate expertise and governance, may produce substantial improvements.
The distinction is important.
We believe that the intelligent transformation of government requires consideration of five connected dimensions.
First, the purpose of the intervention. What public-service problem is being addressed and what measurable improvement is expected?
Second, the quality of the underlying information. Does the department possess the data, institutional knowledge and contextual understanding necessary to use the technology effectively?
Third, the design of the organisation. Are responsibilities, processes, decision rights and professional expertise properly aligned with the proposed application?
Fourth, the management of risk. Are safety, security, privacy, transparency, fairness, reliability and accountability properly understood?
Fifth, the evidence of value. Does the application improve the service, the experience of the citizen, the productivity of public servants or the effectiveness of government expenditure?
These considerations should inform the decision to adopt artificial intelligence, the manner in which it is deployed and the evidence required before it is scaled.
3. THIRTY CONSULTANCY FRAMEWORKS
GENERAL INTELLIGENCE PLC has developed thirty named consultancy frameworks, each addressing a particular conception or application of intelligence and its relevance to a defined industry, professional discipline or organisational environment.
Although developed for specific sectors, the underlying questions have broader relevance to government.
The frameworks examine strategy, customers, products, operations, data, technology, risk, governance, growth and transformation. They provide structured approaches to understanding how information can become intelligence, how intelligence can improve decisions and how organisations can develop the capabilities required to use technology effectively.
They are consultancy frameworks, not thirty separate artificial intelligence products, foundation models or deployed software systems. They should be understood as structured intellectual and strategic approaches to the application of intelligence.
The complete portfolio is as follows.
A. General, organisational and institutional intelligence
1. ABSOLUTE INTELLIGENCE® — Chartered financial analysts
A framework concerned with the quality, reliability and independence of analysis. It examines the testing of assumptions, adversarial assessment, contrary evidence, continuous monitoring and institutional learning.
Its wider relevance to government lies in the importance of evidence-based decision-making, independent scrutiny and the ability to challenge established assumptions.
2. ADAPTIVE INTELLIGENCE® — General insurance
A framework examining how organisations can respond intelligently to changing circumstances. It considers the relationship between historical information, current understanding and emerging conditions.
Its broader relevance is the development of organisations capable of learning continuously rather than relying upon static assumptions, guidance or operating models.
3. ALTERNATIVE INTELLIGENCE® — Alternative investment analysis
A framework concerned with identifying relationships, second-order effects, weak signals and developments that may not be immediately apparent through conventional analysis.
It addresses the importance of looking beyond readily available information and testing prevailing assumptions.
4. APPLIED INTELLIGENCE® — Insurance underwriting
A framework focused on translating information and analysis into practical, defensible decisions.
It considers evidence, assessment, judgement, decision-making, referrals and accountability. Its wider relevance is the movement from technological capability to demonstrable operational application.
5. AUGMENTED® — Insurance
A framework examining how technology can strengthen the capabilities of professionals and organisations rather than simply replace existing activities.
It considers the relationship between human expertise, information, intelligent systems and organisational performance.
6. AUTHENTIC® — Alien abduction insurance
A specialist framework associated with the assessment of authenticity, evidence and provenance in an unusual insurance context.
Its wider intellectual relevance concerns the reliability of information, the distinction between assertion and evidence and the importance of establishing the authenticity of records.
7. AUTONOMOUS® — Life assurance
A framework examining autonomy, delegated authority, institutional control and accountability.
Its relevance to government includes the question of how increasingly automated processes can operate within clearly defined responsibilities and appropriate human oversight.
8. AUTOTELIC® — Yacht insurance
A framework concerned with understanding the purpose, use and operating environment of insured vessels.
Its broader relevance is the importance of understanding the context in which a system or asset operates, rather than assessing its characteristics in isolation.
9. BIONIC INTELLIGENCE® — Managing general agents
A framework examining the relationship between human expertise, delegated authority, technology and institutional control.
It considers how different capabilities can be integrated while maintaining appropriate oversight and responsibility.
10. EMBODIED INTELLIGENCE® — Personal accident insurance
A framework concerned with the relationship between individual circumstances, evidence, human risk and decision-making.
Its broader relevance is the need to understand the real-world context and human consequences of decisions informed by technology.
B. Enterprise, data and organisational capability
11. ENTERPRISE INTELLIGENCE® — Enterprise organisations
ENTERPRISE INTELLIGENCE® is concerned with developing intelligence across an entire organisation.
It examines how information and insight can be translated into coordinated decisions and action, including organisational knowledge, workflows, governance, accountability and institutional learning.
This framework has particular relevance to government departments, where information, expertise and operational responsibilities are frequently distributed across different teams and organisations.
12. EXPONENTIAL INTELLIGENCE® — Redundancy insurance
A framework examining the implications of accelerating economic and technological change for employment-related risk.
Its wider relevance concerns the need for organisations to anticipate structural change, identify emerging consequences and respond before historical data fully reflects new circumstances.
13. FRONTIER INTELLIGENCE® — Offshore energy insurance
A framework addressing complex infrastructure and operational environments, including engineering, subsea operations, offshore energy, environmental conditions and supply-chain dependencies.
Its wider relevance is the management of complex systems in which multiple sources of information and interdependent risks must be understood together.
14. GENERAL INTELLIGENCE® — Asset management
A framework examining how organisations can develop an enduring capacity to understand their environment, assess opportunities, allocate resources and manage risk.
Its wider relevance to government includes strategic planning, resource allocation, institutional knowledge and the quality of decisions made in pursuit of long-term objectives.
15. GENIUS® — Investment banking
A framework concerned with complex analysis, transactions, financial decision-making and professional judgement.
Its wider relevance is the importance of integrating information, specialist knowledge and accountability when decisions have substantial consequences.
16. GENUINE INTELLIGENCE® — Jewellers' block insurance
A framework examining authenticity, provenance, valuation, condition, ownership, custody and security.
Its broader relevance concerns the reliability and provenance of information and the importance of establishing what is genuine before acting upon it.
C. Financial, commercial and specialist intelligence
17. HYPERINTELLIGENCE® — Commercial banking
A framework examining how complex information can improve institutional understanding, including relationships between businesses, markets, transactions, credit, liquidity and risk.
Its wider relevance is the identification of relationships and patterns across large and interconnected information environments.
18. INFINITE INTELLIGENCE® — Kidnap and ransom insurance
A framework concerned with human security, threat assessment, prevention, crisis response and the coordination of specialist expertise.
Its broader relevance is the use of intelligence in complex and rapidly changing circumstances where the quality of decisions may have profound human consequences.
19. INTELLIGENCE® — Retail banking
A framework examining how organisations can develop a deeper understanding of the people and communities they serve.
It considers customer circumstances, financial relationships, services, operational performance and the appropriate use of information.
Its wider relevance includes citizen understanding, service design and the importance of using information to improve the experience of individuals.
20. NEURAL INTELLIGENCE® — General insurance agencies
A framework concerned with organisational learning, professional capability, relationships and the effective use of information.
Its broader relevance is the development of connected organisations in which knowledge can be shared and used to improve performance.
21. REAL INTELLIGENCE® — Fine art and specie insurance
A framework addressing identity, authenticity, provenance, condition, valuation, ownership, location, custody and movement.
Its wider relevance concerns the distinction between a record or representation of an asset and the actual object or circumstance that the record is intended to describe.
22. RECURSIVE INTELLIGENCE® — General reinsurance organisations
A framework examining how organisations learn from differences between prediction and actual experience.
It considers the relationship between assumptions, outcomes, risk, institutional memory and the continuing improvement of future decisions.
Its broader relevance is the importance of feedback, evaluation and systematic organisational learning.
23. REFLECTIVE INTELLIGENCE® — General reinsurance brokers
A framework concerned with independent assessment of technological interventions, alternatives, dependencies and governance.
Its wider relevance is the importance of questioning whether a proposed technological solution is appropriate before committing resources to it.
24. SENTIENT® — Financial advisory
A framework examining the relationship between information, individual circumstances, professional judgement and advice.
Its wider relevance is the importance of preserving human context, responsibility and trust when intelligent systems support decisions affecting individuals.
D. Advanced and emerging intelligence
25. SINGULARITY® — General insurance
A framework considering the implications of technological developments for organisations, emerging risks, changing insurability and the accumulation of exposures.
Its wider relevance is the need to understand how technological change can alter the environment in which institutions operate.
26. SUPERHUMAN® — Risk management
A framework examining how advanced analytical capabilities can extend an organisation's ability to identify complex relationships, emerging threats, concentrations and systemic vulnerabilities.
It also considers the risks created by artificial intelligence itself, including dependency, opacity, data quality, operational resilience and accountability.
27. SUPERINTELLIGENCE® — Financial technology
A framework addressing the strategic implications of advanced intelligence for financial technology organisations.
It examines technology, data, strategy, product development, capital allocation, competitive advantage, governance and transformation.
Its wider relevance is the need to consider how increasingly capable systems may change the nature of organisational decision-making and the capabilities required to manage them.
28. TRUE INTELLIGENCE® — Chartered financial planners
A framework concerned with the relationship between individual circumstances, professional expertise, judgement and long-term objectives.
Its wider relevance is the importance of understanding the people affected by decisions and ensuring that technology supports rather than obscures the responsibilities of those making them.
29. UNIVERSAL INTELLIGENCE® — Film and television production insurance
A framework examining the implications of artificial intelligence and technological developments for film and television production.
It considers intellectual property, provenance, authorship, consent, likeness, contractual obligations and technical dependencies.
Its wider relevance includes the legal, commercial and institutional consequences of the increasing use of synthetic and artificially generated material.
30. X® — Building societies
A framework developed for building societies, examining member intelligence, customer relationships, mortgages, savings, operational performance, governance, community knowledge and institutional memory.
Its wider relevance is the importance of understanding the people and communities an institution exists to serve.
4. THE APPLICATION OF THESE IDEAS TO GOVERNMENT
Although the thirty frameworks were developed for specific sectors, several of their underlying principles have direct relevance to the challenges of government-wide artificial intelligence adoption.
I would draw particular attention to the following areas.
A. Identifying the right problems
Government should begin with the public-service problem rather than the availability of a particular artificial intelligence system.
A department should be able to explain what it is seeking to improve, why the existing approach is inadequate, what evidence supports intervention and what alternative solutions have been considered.
The framework should allow for the possibility that artificial intelligence is not the appropriate answer.
B. Improving institutional intelligence
Government possesses enormous quantities of information, specialist expertise and operational knowledge.
However, the existence of information does not necessarily mean that it is accessible, connected, understood or effectively applied.
The development of institutional intelligence requires departments to understand how knowledge is created, retained, shared and used. It also requires consideration of how institutional memory can be preserved when people, systems and organisational structures change.
C. Learning from implementation
The practical application of artificial intelligence requires continuous evaluation.
Departments should understand what works, what fails, why particular applications succeed and whether the benefits observed in one environment can be reproduced elsewhere.
A system that produces useful results in one department may not necessarily deliver the same results in another. Differences in data, processes, users, responsibilities and operating environments matter.
This makes the ability to learn from implementation and adapt accordingly particularly important.
D. Scaling successful applications
Scaling should not simply mean making a technology available to more departments.
It should involve understanding the conditions under which an application produces value, the requirements for implementation, the risks of wider deployment and the extent to which the underlying processes can be replicated.
A successful application should provide evidence that informs subsequent decisions, rather than becoming an automatic template for every department.
E. Building internal capability
The long-term success of artificial intelligence in government will depend upon the capabilities retained within the public sector.
These include technical expertise, data governance, product management, operational understanding, procurement knowledge, evaluation, security and the ability to assess the performance and limitations of external suppliers.
Government should be an intelligent purchaser and operator of technology, not simply a recipient of technological solutions.
F. Maintaining public trust
The use of artificial intelligence in public services creates responsibilities that extend beyond technical performance.
Government must consider transparency, privacy, fairness, security, explainability, accessibility and the consequences of decisions for individuals.
The appropriate balance between automation and human judgement will differ according to the nature and significance of the service.
Public confidence should be treated as an essential condition of successful implementation.
5. A PROPOSED GOVERNING FRAMEWORK FOR GOVERNMENT AI
In addition to the thirty sector-specific frameworks, I believe there is value in considering a common set of questions that could inform the assessment of artificial intelligence applications across government.
These questions are intended as a practical decision discipline, not as a replacement for existing government guidance, technical standards or statutory responsibilities.
- Purpose: What precisely are we seeking to improve for the citizen, public servant or institution?
- Evidence: What evidence demonstrates that the proposed intervention is likely to produce that improvement?
- Alternatives: Is artificial intelligence the most appropriate means of achieving the objective?
- Information: Is the underlying data sufficiently reliable, relevant, secure and representative?
- Capability: Does the department possess the technical, operational and institutional capability to implement and manage the system?
- Accountability: Who is responsible for the system, its outputs, its limitations and the decisions made using it?
- Risk: What new dependencies, vulnerabilities, liabilities and unintended consequences may arise?
- Evaluation: How will performance, safety, public-service outcomes and value be measured?
- Learning: How will experience, including failure, be captured and used to improve subsequent decisions?
- Scale: What evidence is required before the application is extended to other services or departments?
- Long-term value: Will the intervention strengthen the institution's capabilities and deliver sustainable benefits?
This approach would encourage a disciplined relationship between technological ambition and practical responsibility.
It would also recognise that the correct outcome of an assessment may be adoption, limited deployment, further testing, redesign, an alternative intervention or no deployment at all.
6. THE IMPORTANCE OF BRITISH INTELLECTUAL PROPERTY
There is also a wider national consideration.
The United Kingdom's artificial intelligence ambitions should encompass more than the procurement and adoption of technologies developed elsewhere.
They should include the creation, ownership and development of British intellectual property, specialist expertise, technical capability and institutional knowledge.
The economic and strategic benefits of artificial intelligence will not be distributed automatically. They will depend upon which organisations own the relevant intellectual property, develop the underlying expertise, control important infrastructure and capture the value created through practical application.
GENERAL INTELLIGENCE PLC is a Scottish company established in 1896. The intellectual property and frameworks described in this letter have been developed as part of a British-owned undertaking.
We believe that this provenance is relevant to the wider question of how the United Kingdom develops and retains valuable intellectual assets in an increasingly competitive international environment.
The company has received international interest in aspects of its portfolio, including interest from Silicon Valley and China. We mention this as an indication of the potential wider relevance of the work, not as a representation that any transaction has been concluded or that a particular valuation has been established.
Our intention is to see the portfolio developed constructively, with due consideration to the interests of the United Kingdom.
7. WHY I AM WRITING TO YOU
I appreciate that your responsibilities are operational and strategic and that the Government Digital Service must concentrate on delivering practical improvements rather than accumulating additional theoretical frameworks.
That is precisely why I believe this introduction is relevant.
The thirty consultancy frameworks are intended to provide structured ways of examining intelligence in the context of real organisations, their responsibilities and the environments in which they operate.
They may offer useful perspectives when considering how government departments:
- Identify opportunities for artificial intelligence that address genuine operational and public-service needs.
- Assess the relationship between technological capability and institutional readiness.
- Improve the use of data and organisational knowledge.
- Preserve human expertise and accountability.
- Evaluate the benefits and risks of particular applications.
- Learn from implementation and share successful practice.
- Develop more intelligent and resilient operating models.
I am not suggesting that the frameworks should be imposed upon departments or adopted as central government policy. Nor am I seeking to duplicate existing work undertaken by the Government Digital Service, the Incubator for AI or individual departments.
Rather, I would welcome the opportunity to make the company's intellectual property available for consideration and to establish whether any of the frameworks may complement the work already being undertaken across government.
8. A REQUEST FOR CONSIDERATION
I would be grateful if you would consider this introduction and, if appropriate, arrange for the material to be examined by the relevant colleagues within the Government Digital Service and the Department for Science, Innovation and Technology.
In particular, I would welcome an opportunity to:
- Present the intellectual-property portfolio and its development.
- Explain the purpose and structure of the thirty consultancy frameworks.
- Discuss the distinction between artificial intelligence and institutional intelligence.
- Explore the possible relevance of the frameworks to government-wide AI adoption, service transformation and organisational capability.
- Consider whether there may be an appropriate opportunity for further discussion with the teams responsible for identifying, testing and scaling artificial intelligence applications across government.
I would be pleased to provide the supporting material for each framework, together with the wider intellectual-property portfolio schedule.
I recognise that any consideration would need to be consistent with government priorities, procurement requirements, governance arrangements and established standards for the responsible use of artificial intelligence.
9. CONCLUSION
The opportunity presented by artificial intelligence is not simply to make existing government processes faster. It is to reconsider how the state understands information, delivers services, exercises judgement, allocates resources and learns.
The development of artificial intelligence should therefore be accompanied by a corresponding development in institutional intelligence.
Government must be capable of understanding the technology it uses, identifying where it creates genuine value, recognising where it introduces new risks and retaining the expertise required to manage it responsibly.
GENERAL INTELLIGENCE PLC has sought to address these wider questions through the development of its intellectual-property portfolio and thirty consultancy frameworks.
We believe that this work may offer a useful contribution to the wider discussion about how the United Kingdom can become not merely a country that uses artificial intelligence, but one whose institutions become more intelligent through its application.
Artificial intelligence is a means, not an end. General intelligence is the ambition. Institutional intelligence is the capability. Independent judgement is the discipline. Better government and lasting public value are the objectives.
Thank you for your time and consideration. I would welcome the opportunity to provide further information and to discuss the portfolio with you or the appropriate members of your team.
Yours sincerely,
X from GENERAL INTELLIGENCE PLC