There was a time when I admired Donald J. Trump, not for his policies, but for his apparent resilience. He seemed capable of surviving political, legal, and personal crises that would have ended most careers. His refusal to quit, his instinct to fight back, and his sheer stamina gave the impression of strength.
Over time, however, that impression collapsed.
What once looked like resilience increasingly revealed itself as dominance without discipline, aggression without responsibility, and defiance without purpose. Trump’s behavior consistently demonstrates a lack of conscientiousness: disregard for norms, institutions, truth, and even basic consistency. Loyalty is demanded, but rarely reciprocated. Accountability is avoided, not embraced.
Equally troubling is his emotional instability. Criticism is treated as persecution, disagreement as betrayal, and compromise as weakness. This fuels a pattern of grievance, paranoia, and hostility that poisons discourse rather than leading it. Leadership requires emotional regulation; Trump thrives on emotional escalation.
Most damaging of all is his relentless self-centeredness. Everything becomes about personal victory, personal humiliation, or personal revenge. The public good is secondary to the preservation of ego. When antisocial behavior, lying, intimidation, scapegoating, becomes routine rather than exceptional, admiration turns into disillusionment.
I eventually concluded that what I once mistook for strength was merely survival instinct untethered from character. Trump may be educated and experienced, but education without integrity and experience without responsibility amount to little. In the end, I no longer see a fighter worthy of respect, only someone endlessly struggling to protect himself, offering nothing larger than that struggle.
Artificial Intelligence is no longer a speculative technology on the horizon: it is an operational reality reshaping economies, institutions, and human work. While most discussions about AI focus narrowly on tools, models, or short-term productivity gains, the true future of AI is broader and more consequential: AI is evolving from a passive instrument into an active cognitive partner embedded across society. Understanding this transition is essential for leaders, professionals, and policymakers who want to remain relevant in an AI-driven world.
1. From Narrow Automation to Generalized Intelligence
Early AI systems were designed to perform narrowly defined tasks, recognizing images, translating text, or optimizing logistics. The next phase is characterized by generalized capability, systems that can reason across domains, adapt to new contexts, and collaborate with humans in complex problem-solving.
Key shifts include: Multimodal intelligence (text, image, audio, video, and action); Persistent memory and long-term context; Autonomous goal decomposition and planning; Self-improvement through feedback loops. This does not imply human-level consciousness, but it does mean human-comparable competence across many cognitive tasks.
2. AI as a Cognitive Infrastructure
AI is becoming a foundational layer, similar to electricity or the internet, rather than a standalone product. In the future, AI will be: Embedded invisibly in workflows; Integrated into decision-making systems; Continuously adaptive to users and environments. Organizations will not ask “Should we use AI?” but rather “How is intelligence flowing through our systems?” Competitive advantage will come from orchestrating intelligence, not merely adopting tools.
3. The Transformation of Work and Expertise
In the coming years, AI will not simply eliminate jobs; it will redefine expertise. Routine cognitive labor will be increasingly automated, while human value will concentrate in areas where: Judgment under uncertainty matters; Ethical, social, and contextual reasoning is required; Creativity and strategic synthesis are essential; Accountability and trust are critical.
The most valuable professionals will be those who can: Think systemically; Ask high-quality questions; Supervise and align AI systems; Translate between technical, business, and human domains. In short, the future belongs to AI-augmented professionals, not AI-replaced ones.
4. Governance, Trust, and Alignment
As AI systems gain autonomy and scale, governance becomes a central challenge. The future of AI will be shaped as much by policy and ethics as by technology. Critical issues include: Model transparency and explainability; Bias, fairness, and representational harm; Data ownership and privacy; Accountability for AI-driven decisions; Alignment with human values and societal goals.
Nations and organizations that establish trustworthy AI frameworks will gain long-term legitimacy and public acceptance.
5. The Rise of Personal and Collective AI
We are moving toward a world where individuals have persistent personal AI agents, teams collaborate with shared AI copilots and organizations operate with collective intelligence systems.
These systems will learn individual preferences and goals, act as cognitive extensions of the user and coordinate knowledge across groups at scale. This represents a fundamental shift in how humans think, learn, and collaborate.
6. Risks, Limits, and Reality Checks
Despite rapid progress, AI is not magic. The future will include technical limitations and failures, over-reliance and skill atrophy, concentration of power among a few actors and misuse in surveillance, manipulation, and conflict.
Responsible progress requires clear-eyed realism, not blind optimism or reflexive fear.
Choosing the Future of AI
The future of AI is not predetermined. It will be shaped by how organizations deploy it, how governments regulate it, how professionals adapt to it and how society defines acceptable use.
AI’s ultimate impact will depend less on what the technology can do, and more on what we choose to do with it. Those who engage early, thoughtfully, ethically, and strategically, will help define an AI-enabled future that amplifies human potential rather than diminishes it.
J. Michael Dennis ll.l., ll.m.
Based in Kingston, Ontario, Canada, J. Michael Dennis is a former barrister and solicitor, a Crisis & Reputation Management Expert, a Public Affairs & Corporate Communications Specialist, a Warrior for Common Sense and Free Speech. Today, J. Michael Dennis help executives and professionals understand, evaluate, and responsibly deploy AI without hype, technical overload, or strategic blindness.
A Consultant’s Perspective on What Actually Matters
As an AI Consultant, I spend far less time discussing models, benchmarks, or product launches than most people expect. Those details matter, but they are not where the real transformation is happening.
The future of Artificial Intelligence will not be decided by algorithms alone. It will be decided by how organizations, leaders, and institutions choose to integrate intelligence into their decision-making, operations, and culture.
From the field, the signal is clear: AI is moving from a tool you “use” to a system you work with.
1. AI Is Becoming Strategic Infrastructure, Not Software
Most organizations still approach AI as a technology purchase. That mindset is already obsolete. AI is rapidly becoming cognitive infrastructure, a layer that influences: How decisions are made; How work is coordinated; How knowledge flows across the organization; How risks are identified and mitigated.
In the near future, competitive advantage will not come from having access to AI (everyone will), but from how intelligently it is embedded into business processes and governance structures.
This is not an IT problem. It is a leadership problem.
2. The Real Shift: From Automation to Augmentation
The dominant narrative focuses on job displacement. In practice, what I observe is something subtler and more disruptive: the redefinition of expertise.
AI excels at: Pattern recognition; Synthesis at scale; Speed and consistency. Humans remain essential for: Judgment under uncertainty; Contextual and ethical reasoning; Strategic prioritization; Accountability.
The future belongs to professionals who can collaborate with AI systems, supervise them, and translate their outputs into real-world decisions. Organizations that fail to reskill their people around this reality will fall behind, regardless of how advanced their tools appear.
3. Why Most AI Initiatives Fail
From a consulting standpoint, AI failures rarely stem from weak models. They stem from: Poor problem definition; Misaligned incentives; Lack of data governance; Absence of ownership and accountability; Unrealistic expectations driven by hype.
Successful AI adoption requires discipline: Clear use cases tied to measurable outcomes; Human-in-the-loop design; Change management, not just deployment; Continuous evaluation and iteration.
AI is not a one-time implementation. It is an ongoing organizational capability.
4. Trust, Governance, and the Consultant’s Blind Spot
As AI systems gain autonomy, trust becomes the limiting factor.
Leaders increasingly ask: “Can we explain this decision?”; “Who is accountable if this goes wrong?”; “Are we exposing ourselves to legal or reputational risk?”
The future of AI will be constrained, and/or enabled, by governance. Consultants and leaders who ignore this dimension are setting their organizations up for long-term failure.
Responsible AI is not a moral luxury; it is a strategic necessity.
5. The Rise of Personal and Organizational AI Agents
We are entering a phase where AI will be persistent, personalized, and proactive.
In practical terms: Executives will work with AI advisors; Teams will share AI copilots; Organizations will develop collective intelligence systems.
The consultant’s role will evolve accordingly: from recommending tools to architecting intelligence ecosystems aligned with strategy, culture, and values.
6. What Leaders Should Be Doing Now
From my perspective, the organizations that will thrive are already: Treating AI as a board-level topic; Investing in AI literacy across leadership; Designing governance before scaling deployment; Experimenting in controlled, high-impact areas; Focusing on augmentation, not replacement.
Waiting for “mature” AI is a strategic error. Maturity comes from engagement.
Conclusion: AI Will Reward Clarity, Not Hype
The future of AI will not favor the loudest adopters or the most aggressive automators. It will favor those who approach AI with clarity of purpose, discipline of execution, and respect for human judgment.
As an AI Consultant, my role is not to sell technology, it is to help organizations think clearly about intelligence: how it is created, governed, and applied. Those who do this well will not just survive the AI transition. They will shape it.
J. Michael Dennis ll.l., ll.m.
Based in Kingston, Ontario, Canada, J. Michael Dennis is a former barrister and solicitor, a Crisis & Reputation Management Expert, a Public Affairs & Corporate Communications Specialist, a Warrior for Common Sense and Free Speech. Today, J. Michael Dennis help executives and professionals understand, evaluate, and responsibly deploy AI without hype, technical overload, or strategic blindness.
J. Michael Dennis ll.l., ll.m. Live 
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