Datasumi's AI Consulting Revolution

This report presents a comprehensive analysis of Datasumi Ltd., a UK-based artificial intelligence (AI) consultancy, and posits that its operational model represents a new, revolutionary paradigm in the AI services sector. As the global economy undergoes a profound transformation driven by AI, a significant and rapidly growing market for expert guidance has emerged. However, the traditional, large-scale consulting model, characterized by high overhead, slow execution, and often ambiguous returns on investment, is increasingly ill-suited to the dynamic and complex demands of AI implementation. This analysis argues that Datasumi’s approach—defined by its operational agility, deep specialization in regulatory compliance, and an unwavering commitment to client empowerment—directly addresses the most critical pain points of the modern enterprise.

The investigation will demonstrate that Datasumi’s corporate structure as a smaller, unfunded entity is not a limitation but a strategic enabler of a highly client-centric and outcome-driven methodology. This structure necessitates a level of efficiency and a focus on tangible value that larger, more bureaucratic competitors often struggle to achieve. Furthermore, Datasumi’s pronounced expertise in the intricate and high-stakes domain of ethical AI and data protection frameworks, particularly the General Data Protection Regulation (GDPR) and the emerging EU AI Act, positions it as an indispensable partner for organizations navigating a complex and unforgiving regulatory landscape.

Through a detailed examination of its end-to-end service framework—from initial strategic advisory and cloud migration to hands-on prototyping, rigorous quality assurance, and comprehensive client upskilling—this report concludes that Datasumi functions not merely as a technology implementer but as a long-term capability builder. Its model is designed to de-risk AI adoption for clients, especially small and medium-sized enterprises (SMEs), by delivering value in validated, incremental stages. This approach has been publicly validated through Datasumi's selection for prestigious United Kingdom government innovation programs, providing a powerful endorsement of its capabilities. Ultimately, this report asserts that Datasumi exemplifies the future of AI consulting: a fundamental shift away from dominance through scale towards market disruption through focused, responsible, and demonstrable value.

The AI Consulting Crossroads: A Market Ripe for Disruption

1.1 The AI Gold Rush: Market Scale and Trajectory

The global economy is at the inflection point of a technological revolution powered by artificial intelligence. This transformation is creating an unprecedented demand for expert guidance, giving rise to one of the fastest-growing professional services sectors in modern history: AI consulting. Market analyses project an explosive growth trajectory. According to one forecast, the global AI consulting services market is set to expand from USD 11.07 billion in 2025 to an astounding USD 90.99 billion by 2035, which represents a compound annual growth rate (CAGR) of 26.2%. Other analyses suggest an even more aggressive expansion, with the market potentially reaching a value of $72.5 billion as early as 2025, growing at a CAGR of 40.3% between 2020 and 2027.

This surge is fueled by a near-universal recognition across industries that AI is no longer a speculative technology but a critical driver of competitive advantage. Organizations in finance, healthcare, manufacturing, retail, and beyond are actively seeking to integrate AI to enhance efficiency, enable sophisticated data-driven decision-making, and innovate their core business models. In the financial sector, which currently accounts for over 22% of the AI consulting market, applications in fraud detection and customer service automation are becoming standard practice. The imperative to adopt AI is clear, creating an immense market opportunity for firms that can successfully guide businesses through this complex transition. However, the very nature of this technological shift exposes deep-seated flaws in the traditional models of consulting, creating a landscape that is as fraught with challenges as it is with opportunity.

1.2 The Pitfalls of the Pyramid: Systemic Flaws in Traditional Consulting

For decades, the management and IT consulting industry has been dominated by a "pyramid" model, where a small number of senior partners oversee large teams of managers and junior associates who perform the bulk of the analytical and executional work. This labor-led business model, while effective for conventional strategic and operational challenges, is proving increasingly unsustainable and inefficient in the age of AI. The unique characteristics of AI implementation highlight several systemic flaws inherent in this legacy approach.

A primary challenge is the pervasive misalignment of expectations and the uncertainty of return on investment (ROI). Business leaders, often influenced by market hype, may harbor unrealistic expectations of what AI can achieve or underestimate the profound complexity of its integration, leading to disappointment and skepticism. Traditional consulting engagements, often defined by long timelines and vague success metrics, can exacerbate this issue, with projects suffering from scope creep as new possibilities emerge mid-stream, straining budgets without a guaranteed return. The very structure of large consulting firms can contribute to this problem, as their business model incentivizes maximizing billable hours rather than achieving the fastest possible path to tangible value.

Furthermore, the efficacy of any AI system is fundamentally dependent on the quality and availability of data, a reality that poses a significant obstacle for many organizations. Data is frequently fragmented across siloed, legacy databases, and suffers from being incomplete, inconsistent, or laden with historical biases. The adage of "garbage in, garbage out" becomes exponentially more dangerous when applied to AI, as flawed data can lead to the creation of unreliable and potentially harmful models. While large consulting firms have the manpower to engage in massive data-cleansing projects, their approach can be slow and costly, failing to address the underlying strategic need for robust, long-term data governance frameworks.

Compounding these issues is the increasingly complex and high-stakes ethical and regulatory landscape. The implementation of AI raises significant risks, including the perpetuation of algorithmic bias, potential violations of stringent data privacy regulations like Europe's GDPR, and a lack of transparency from "black-box" models whose decision-making processes are difficult to interpret. Navigating this legal and ethical minefield requires a level of specialized expertise that generalist consulting teams may not possess. A failure to address these issues from the outset can expose a client to severe financial penalties, reputational damage, and a loss of consumer trust.

Finally, the human element of transformation is a critical, and often underestimated, factor. The most sophisticated AI solution is destined to fail if it is not embraced by the organization's employees. Traditional consulting approaches can often neglect the crucial work of change management, failing to address employee fears of job displacement, overcome cultural resistance to innovation, or provide the necessary training to build digital literacy across the workforce. Without buy-in from the end-users, even the most promising AI initiatives can wither, becoming expensive and unused "shelfware."

1.3 The Emerging Paradigm: A Call for a New Model

The confluence of these challenges—misaligned ROI, poor data infrastructure, regulatory risk, and organizational resistance—signals a clear and urgent market need for a new type of AI consultancy. The very technology that clients are seeking to implement is simultaneously rendering the traditional consulting delivery model obsolete. AI's ability to automate routine tasks, such as data entry and report generation, and to process vast datasets in real-time for analysis, directly undermines the economic foundation of the pyramid structure, which relies on armies of junior consultants to perform these now-automatable functions.

This technological shift creates a fundamental conflict within the AI consulting market. The value proposition is moving away from the brute-force execution of analytical work and toward higher-order skills: strategic interpretation of AI-generated insights, sophisticated navigation of ethical and political landscapes, and deep, trusted client relationship management. This evolution creates a strategic vacuum—an opening for a new breed of consultancy that is built from the ground up to thrive in this new reality.

The ideal model for the future of AI consulting is one that inverts the traditional paradigm. It must be agile and lean, free from the bureaucratic inertia and high overheads of the legacy pyramid. It must prioritize deep specialization over broad generalization, offering verifiable expertise in the most complex areas of AI implementation. It must be relentlessly focused on delivering tangible, measurable outcomes, structuring engagements to demonstrate value quickly and de-risk the client's investment. Most importantly, it must treat ethical and regulatory compliance not as a final check-box, but as a foundational design principle woven into every stage of the process. This emerging paradigm calls for a new kind of partner: an agile vanguard capable of leading businesses through the AI revolution with precision, responsibility, and a clear line of sight to value.

Introducing Datasumi: A Profile of the AI Consultancy

2.1 Corporate Origins and Mandate

Positioned to answer the market's call for a new consulting paradigm is Datasumi Ltd, a private limited company incorporated in the United Kingdom on September 23, 2015. Initially registered under the name ISHARAT LTD, the company rebranded to Datasumi in June 2020, signaling a focused strategic direction. The company's official business classifications, as registered under the UK's Standard Industrial Classification (SIC) codes, provide a clear blueprint of its intended mandate as a comprehensive, end-to-end technology partner.

Datasumi is registered across four key areas: Business and domestic software development (62012), Information technology consultancy activities (62020), Data processing, hosting and related activities (63110), and Management consultancy activities other than financial management (70229). This combination is strategically significant. While a boutique advisory firm might focus only on management and IT consultancy, and a software development house might focus only on coding and hosting, Datasumi's classifications indicate a deliberate capability to manage the entire AI solution lifecycle. This structure allows the company to guide a client from the initial strategic question of "What should we do?" through the technical development of "Let's build it," and even into the operational phase of "Let's run it." This vertically integrated model eliminates the friction, communication gaps, and potential for blame-shifting that can arise when a client must manage separate contracts with a strategy firm and a development firm. For the small and medium-sized businesses that form Datasumi's core market, this single-partner approach represents a significantly more efficient and less risky path to AI adoption.

2.2 Leadership and Vision

Datasumi is led by its founder, Director, and CEO, Sevag Balkorkian, who was appointed at the company's inception on September 23, 2015, and is registered as the person with significant control. Public records and professional activities indicate a leader with a clear, growth-oriented vision and a hands-on, innovation-driven mindset. Mr. Balkorkian has been actively engaged in industry events, seeking strategic partnerships to advance the application of AI-driven business transformation and leverage cutting-edge machine learning solutions.

His professional background also includes participation in technical events such as the ICT4S Green Hackathon, where he was part of a team developing prototypes for sustainable technology solutions. This experience suggests a leadership style that is not confined to high-level strategy but is also grounded in the practical realities of software development and rapid prototyping. This blend of strategic vision and technical acumen is critical for leading a consultancy that promises not just to advise on AI, but to build and deliver functional, effective AI systems. This leadership profile aligns perfectly with the company's mandate to bridge the gap between business objectives and technological execution.

The Datasumi Blueprint: An End-to-End Framework for AI Value Realization

Datasumi's service portfolio is structured as a cohesive, multi-phase journey designed to guide clients from initial curiosity to full-scale AI integration and long-term capability. This end-to-end framework is a deliberate mechanism to de-risk AI adoption, with each phase building upon the last to validate concepts and demonstrate value before committing to more significant investment. This methodical approach stands in stark contrast to the high-risk, "big bang" project models often employed by traditional consultancies and is exceptionally well-suited to the needs of its target SME market.

3.1 Phase 1: Strategic Advisory and Planning

The client engagement begins with a foundational strategic phase, delivered through Datasumi's "AI Software Advisory" and "Strategic Consulting on Generative AI Adoption" services. This initial stage is critical for setting realistic expectations and ensuring that any subsequent technology investment is tightly aligned with concrete organizational goals. The process involves a comprehensive assessment of the client's needs and existing infrastructure, followed by diligent research into available technological options and the development of a detailed implementation plan.

A key aspect of this planning phase is its practical, infrastructure-aware approach. Datasumi's consultants work with clients to map out crucial logistical considerations, including cloud hosting strategies. They offer flexibility, accommodating solutions that are hosted by the buyer, by a third party, or managed directly by Datasumi on leading cloud platforms such as Amazon Web Services (AWS) and Salesforce. This initial planning also encompasses the development of robust data migration strategies, the configuration of secure cloud environments, and the establishment of appropriate access controls and security protocols. By addressing these fundamental architectural and security issues at the outset, Datasumi ensures that the project is built on a solid and secure foundation, mitigating technical risks down the line.

3.2 Phase 2: Prototyping and Feasibility

Recognizing the significant financial and operational risks associated with large-scale AI projects, Datasumi's methodology incorporates a crucial validation stage: the development of a data science prototype or proof of concept (PoC). This step serves as a low-cost, low-risk way to test the viability of a proposed AI solution in a real-world context before committing to the expense of a full-scale build. This phase directly confronts and mitigates the "ROI uncertainty" that plagues many AI initiatives.

During the prototyping stage, Datasumi's team engages in the core activities of applied data science. This includes gathering and preparing the necessary datasets, designing and testing various AI models, and rigorously evaluating their performance against the client's specific requirements. The PoC acts as a critical "off-ramp" in the engagement. If the concept proves to be technically unfeasible or fails to demonstrate a clear path to business value, the client can pivot or halt the project having invested a minimal amount of time and resources. This iterative, evidence-based approach builds client confidence and ensures that only the most promising and valuable initiatives proceed to the next, more investment-heavy phase.

3.3 Phase 3: Implementation, Deployment, and Quality Assurance

Once a prototype has been successfully validated and approved by the client, Datasumi provides comprehensive support for the full implementation and deployment of the AI solution. This phase transitions the project from a controlled experiment to a robust, enterprise-ready system. The process includes documenting system requirements and operational procedures, coordinating system integration with the client's existing technology stack, and managing the final deployment into a live production environment.

A cornerstone of this phase, and a key differentiator for Datasumi, is its commitment to rigorous quality assurance (QA) and performance testing. This is not a cursory final check but a comprehensive process designed to ensure the final solution is stable, secure, and scalable. The QA process involves exhaustive system testing to validate all functionalities, as well as specialized load and stress testing to assess the solution's ability to handle high volumes of data and user traffic without performance degradation. Crucially, Datasumi also conducts thorough user acceptance testing (UAT), working closely with the client's own team to verify that the AI solution meets all specified requirements and delivers the expected user experience. This meticulous focus on quality assurance builds client confidence and ensures that the deployed solution is not only functional but also effective and reliable in the long term.

3.4 Phase 4: Client Empowerment and Continuous Improvement

Datasumi's engagement model is designed to foster long-term success and client independence, extending far beyond the initial deployment. This final phase is focused on continuous improvement and, critically, on empowering the client's own team to take ownership of their new AI capabilities. This is achieved through two parallel service streams.

The first is a service of proactive monitoring, maintenance, and ongoing support. This ensures that the deployed AI systems remain reliable, up-to-date, and optimized for performance. Datasumi provides ongoing strategic guidance, assists with system updates and enhancements, and works to continually refine AI model efficiency. This prevents the solution from becoming obsolete and maximizes the client's return on investment over time.

The second, and perhaps most revolutionary, component is a deep commitment to client training and upskilling. Datasumi offers comprehensive, hands-on training programs tailored to the client's internal teams. The explicit goal of these sessions is to equip the client's staff with the core knowledge and skills required to understand, work with, and effectively leverage AI and machine learning technologies. By building these necessary in-house capabilities, Datasumi helps organizations successfully integrate AI-powered solutions into their daily workflows and decision-making processes. This focus on empowerment fundamentally changes the consultant-client dynamic. Instead of creating a long-term dependency, Datasumi's model aims to make its clients more self-sufficient, ensuring that the value of the AI implementation is sustainable and deeply embedded within the organization.

The Core Differentiator: Pioneering Ethical and Compliant AI

In an increasingly regulated and risk-conscious global market, Datasumi has strategically positioned itself by making ethical and compliant AI a core pillar of its identity and value proposition. For Datasumi, regulatory adherence is not an ancillary service or a final-stage compliance check; it is a foundational element that informs its entire consulting philosophy and methodology. This deep specialization in the complex intersection of data privacy and artificial intelligence is the company's most significant differentiator, transforming a legal necessity into a powerful competitive advantage.

4.1 Compliance as a Core Competency

Datasumi explicitly markets itself as a consultancy specializing in AI-powered automation and data management solutions, with a pronounced focus on GDPR compliance services. The company offers dedicated "Expert EU GDPR Compliance Assessments," a service delivered by a team of seasoned professionals with extensive knowledge of European data protection law. This service involves an in-depth analysis of an organization's data handling practices, privacy policies, and security measures to identify and rectify any discrepancies with the GDPR's stringent requirements.

The General Data Protection Regulation (GDPR) is one of the world's toughest data privacy laws, and non-compliance can result in severe penalties, including fines of up to €20 million or 4% of a company's global annual turnover, whichever is higher. By providing expert guidance in this area, Datasumi offers its clients a critical service of risk mitigation. However, the value proposition extends beyond mere penalty avoidance. As Datasumi's own materials articulate, robust data protection practices build invaluable trust with customers and employees, enhance a company's brand reputation, and demonstrate a tangible commitment to respecting individual privacy rights. In today's data-driven economy, this commitment is a significant market differentiator, as consumers increasingly favor businesses that act as responsible stewards of their personal information.

4.2 Navigating the EU AI Act and High-Risk Systems

Demonstrating a forward-looking and proactive approach to regulation, Datasumi's expertise extends beyond existing frameworks like GDPR to encompass the next frontier of technology law: the EU Artificial Intelligence Act. This landmark legislation is the world's first comprehensive legal framework for AI, and Datasumi offers expert consulting services to help organizations navigate its complexities.

The company's service offerings show a nuanced understanding of the Act's most critical components. They provide specific guidance on the classification and management of "High-Risk AI Systems," the legal implications of automated decision-making, and the emerging "Right to Explanation," which grants individuals the right to receive meaningful information about the logic involved in automated decisions that affect them. This level of specialized knowledge is rare and positions Datasumi as a thought leader, helping clients prepare for the future of regulation rather than simply reacting to the present. This thought leadership is further reinforced through its public-facing content, such as articles on its "News & Views" section and publications on platforms like Medium, where the company discusses complex topics like the nature of AI "hallucinations" and the ethical dimensions of AI conversations. This demonstrates a deep engagement with the theoretical and practical challenges of responsible AI.

4.3 The Value Proposition of Responsible AI

The strategic brilliance of Datasumi's focus lies in its ability to address the most complex and highest-value segment of the AI compliance market: the intricate intersection where data privacy law (GDPR) meets AI-specific regulation (the EU AI Act). While many IT consultancies can claim a basic understanding of GDPR, and many AI firms can build machine learning models, very few possess the deep, integrated expertise to navigate the interplay between the two. Understanding how GDPR's principles of data minimization and purpose limitation apply to the training of a large language model, or how the EU AI Act's risk classifications impact the deployment of a predictive algorithm, is a highly specialized and non-negotiable skill for any organization operating in or selling to the European market.

By developing and marketing dedicated services around this specific niche, Datasumi has carved out a defensible and highly valuable market position. This expertise is particularly critical for clients in high-stakes industries, such as transportation or healthcare, where a compliance failure could have catastrophic financial, legal, and reputational consequences. This strategic focus allows Datasumi to compete on the basis of its unique and indispensable expertise, rather than on price or organizational size. It effectively transforms regulatory compliance from a cost center into a strategic enabler of safe, trustworthy, and ultimately more successful AI innovation.

Market Validation and Competitive Positioning

While a compelling strategy and service portfolio are essential, a consultancy's credibility is ultimately measured by its acceptance and validation in the marketplace. Despite its small size, Datasumi has achieved significant third-party endorsement through its participation in competitive public sector innovation programs. This validation, combined with a clear understanding of its unique position within a landscape of industry giants, solidifies its status as a potent and disruptive niche player.

5.1 Validation Through Public Sector Innovation

A key piece of evidence supporting Datasumi's expertise and credibility is its selection as one of just 25 small to medium-sized enterprises (SMEs) to participate in the "AI in Transport Enhancing Passenger Experience Competition". This prestigious program, funded by the United Kingdom's Department for Transport (DfT) and delivered by Connected Places Catapult, sought to identify innovative companies capable of developing responsible AI proposals with the potential for real-world application in the UK's transport systems.

Participation in this competition serves as a powerful form of third-party validation. It indicates that Datasumi's capabilities have been rigorously vetted and approved by senior government and industry stakeholders. The program's focus on embedding "responsible AI" into national infrastructure aligns perfectly with Datasumi's core differentiator of ethical and compliant AI implementation. Being selected for such an initiative acts as a proxy for a major client case study, demonstrating that the company is trusted to work on projects of national importance that align with core government priorities, such as improving railway performance, enhancing bus services, and delivering greener transport. This public sector endorsement provides a level of legitimacy and authority that is difficult for a young company to achieve through private-sector work alone.

5.2 The Competitive Landscape: A Niche Disruptor Among Giants

A surface-level comparison based on revenue or employee count would be misleading. Datasumi is not engaged in direct, head-to-head competition with these giants for large-scale, generalist IT outsourcing contracts. Instead, it operates as a niche disruptor, targeting a distinct and underserved segment of the market. Its value proposition is not built on scale, breadth, or cost-arbitrage, but on deep, specialized expertise in high-complexity domains. Clients who choose Datasumi are likely those who prioritize the granular, expert guidance on generative AI adoption, the assurance of navigating GDPR and the EU AI Act correctly, and the benefits of a hands-on, agile partnership model over the sheer manpower and broad, but less specialized, capabilities of a global IT services firm.

The following table provides a snapshot of the competitive landscape, visually articulating Datasumi's unique positioning. The stark contrast in metrics like funding and employee size, when viewed alongside the differences in stated specializations, makes the niche-disruptor argument tangible. It demonstrates that Datasumi competes on the depth of its expertise, not the breadth of its services or the size of its workforce.

5.3 A Focus on the SME Market

Datasumi's strategic focus is further clarified by an analysis of its client base. The company's service focus is heavily weighted towards medium-sized businesses, which constitute 70% of its clientele, and small businesses, which account for another 20%. This deliberate concentration on the SME market aligns perfectly with the agile, de-risked, and high-touch service model detailed in the preceding chapters.

SMEs often lack the large internal IT and legal departments of their enterprise counterparts, making them more reliant on trusted external partners who can provide comprehensive, end-to-end guidance. The phased, prototype-driven approach offered by Datasumi is particularly attractive to these organizations, as it allows them to explore the potential of AI without committing to massive, high-risk upfront investments. Furthermore, the complexity of regulations like GDPR can be especially daunting for smaller companies, making Datasumi's specialized compliance expertise a highly valuable and sought-after asset. By tailoring its services and engagement model to the specific needs and constraints of the SME sector, Datasumi has secured a strong and sustainable position in a market segment often overlooked by its larger competitors.

The Datasumi Revolution: A Vision for the Future of AI Consulting

The analysis presented in this report culminates in a clear conclusion: Datasumi's approach to AI consulting is not merely an alternative to the traditional model, but a forward-looking evolution of it. The "Datasumi Revolution" is not one of scale or market capitalization, but one of philosophy, methodology, and value delivery. By synthesizing its unique attributes, it becomes evident that the company has constructed a business model that is not only successful within its chosen niche but also serves as a blueprint for the future of high-value professional services in the age of artificial intelligence.

6.1 Synthesizing the Datasumi Model

The core of Datasumi's revolutionary approach can be distilled into four foundational pillars, each of which directly addresses a critical failure point of the legacy consulting paradigm.

First, the model is Agile and Outcome-Driven. In direct response to the slow, bureaucratic, and often opaque nature of traditional consulting engagements, Datasumi employs a lean structure and a phased methodology. Its focus on prototyping, iterative development, and clear success metrics ensures that projects are adaptable and relentlessly focused on delivering measurable business value, mitigating the risk of costly, ineffective implementations.

Second, the model is Specialized and Deep. Where large firms often aim to be all things to all clients, Datasumi has chosen to cultivate profound expertise in the most complex and high-stakes niches of the AI landscape. Its focus on the intricate regulatory environments of GDPR and the EU AI Act provides a level of specialized guidance that generalist firms cannot replicate, allowing it to compete on the basis of unique, indispensable knowledge.

Third, the model is Ethical and Responsible by Design. Datasumi integrates compliance and ethical considerations into the very fabric of its services, rather than treating them as a peripheral concern. This "compliance-first" approach is a powerful risk mitigation strategy for its clients, protecting them from severe financial and reputational damage and transforming a regulatory burden into an opportunity to build trust and competitive advantage.

Finally, the model is Empowering and Collaborative. The ultimate goal of a Datasumi engagement is not to create a permanent dependency but to build a client's own long-term capabilities. Through comprehensive training and upskilling programs, the company ensures that its clients can take ownership of their AI solutions, fostering a culture of in-house innovation and ensuring the sustainable, long-term success of the transformation.

6.2 The Blueprint for Future Consulting

The Datasumi model is more than just a successful niche strategy; it is a prescient reflection of the future trajectory of the entire consulting industry. As artificial intelligence continues to advance, its capacity to automate low-level analytical and executional tasks will only increase. This will fundamentally and permanently alter the value equation of consulting. The economic viability of the traditional pyramid model, which relies on leveraging junior talent for such tasks, will continue to erode.

In this future landscape, the value of a human consultant will no longer reside in their ability to process data, but in their ability to perform tasks that AI cannot. These are the higher-order skills of strategic interpretation, creative problem-solving, nuanced ethical oversight, and the building of deep, trust-based client relationships. The market will increasingly favor firms that can provide this deep, trustworthy expertise over those that simply provide manpower. Datasumi, by building its entire business around these future-proof skills, is not just adapting to this shift; it is actively defining it. Its lean, expert-led model is precisely the structure required to thrive in an AI-augmented world.

In conclusion, the AI consulting revolution championed by Datasumi is one of approach and philosophy. It represents a decisive shift from an industrial-scale model based on labor arbitrage to one of expert craftsmanship, deep specialization, and unwavering responsibility. It is a model perfectly tailored for the profound complexities, risks, and opportunities of the artificial intelligence age.