Quantum Strategy Evolution
AI's Impact Today
Full transparency, I use GPT’s (at least 3 different ones) every day. Do I rely on them blindly? 100% no. I’ve corrected them constantly not because I have special skills rather because I’m scanning numerous different sources (including the current day’s) all the time to find the latest information, trend and corrections. And I’ve lived through my share of AI winters, so I recognize hype and its’ downfalls.
So where does that leave a quantum strategy enthusiast (including business leaders) looking to GPT’s for guidance in 2025?
Solidly on the fence. Here’s why.
Image source: Brian Lenahan/Midjourney
Learning From AI’s Evolution
AI Winters
The term AI winter refers to recurring periods of reduced funding, waning public interest, and slowed progress in artificial intelligence research, beginning in the 1970s after early optimism—spurred by perceptrons and symbolic reasoning—faded when researchers hit computational and theoretical limits. A second, more severe AI winter began in the late 1980s and early 1990s, triggered by the collapse of the expert systems market, unmet expectations, and critical reports such as the UK’s Lighthill Report (1973) and DARPA’s funding cuts. Since the late 1990s, advances in machine learning, data availability, and computing power (notably deep learning in the 2010s) reignited enthusiasm, leading to today’s AI boom. However, cycles of hype and disillusionment remain, with current debates about overpromising, regulation, and the sustainability of progress raising concerns that another AI winter—though likely shorter and more sector-specific—could still emerge.
AI’s Future
Generative AI, AI agents, superintelligence…the list of AI’s evolutionary points are long. Unfolding through a series of milestones, the makers of AI (including AI itself) promise to progressively expand its capabilities and societal impact: in the near term (2025–2030), expect rapid integration of AI copilots across industries, advances in multimodal systems, and regulation frameworks shaping responsible use (albeit challenging to enforce); by the early 2030s, AI could achieve more general reasoning abilities, enabling autonomous scientific discovery, personalized education, and breakthroughs in healthcare diagnostics and drug design; mid-century (2040s–2050s), progress toward artificial general intelligence (AGI) may emerge, with machines demonstrating flexible problem-solving across domains, raising profound ethical and governance challenges; beyond 2050, if safe development continues, AI could become a core partner in human creativity, governance, and planetary-scale problem-solving such as space exploration—making the trajectory less about whether AI advances, and more about how society manages its risks and distributes its benefits.
The Quality of GPT’s
Accuracy is measured in many ways, yet the most relevant measure is how a GPT serves your purposes, not whether the GPT is ‘technically accurate’. It must be or become contextually accurate. One measure is the Massive Multitask Language Understanding (MMLU) benchmark which is becoming a standard for evaluating AI accuracy across diverse subjects (e.g., math, science, history). Higher scores indicate better general knowledge and reasoning.
The following table includes examples of various GPT’s and their accuracy level based on the MMLU approach:
Image source: ChatGPT
Accuracy varies significantly by task. For example, GPT-3.5’s low performance in chemistry (25%) highlights its weakness in specialized domains like quantum computing, while GPT-4.5’s 89.3% MMLU score reflects stronger general capability. Real-world accuracy depends on prompt clarity and topic specificity. Compare models for your specific use cases.
Here’s a specific example of the accuracy challenge, and why we should not depend solely on a GPT:
I asked one GPT in July 2025 for the view of Magnificent 7 leaders on quantum computing. Its response included a view from Jensen Huang, CEO of Nvidia from a February 2025 conference where he argued the technology was 10-15 years away. The result was the plummeting of pure public quantum stocks overnight.
The issue? By May 2025, Huang had not only altered his view, but hosted a quantum summit to emphasize his more positive position. Anyone using a GPT based solely on the first response would be misguided.
My reaction? I reminded the GPT about the latter events. What did it do? It apologized for not referring to the latter events and updated its response. OK, well done you, but for those with less knowledge of the industry, you’re not just being inconvenienced, but rather misdirected.
The world of quantum technologies is changing so rapidly that any brief contextual summary from a GPT is insufficient to keep up to date. Is it important to do so? With so many different breakthroughs, modalities, platforms, use cases and more changing regularly, end users will be hard pressed to stay current.
Your Best Approach
There’s room for the human-AI hybrid even in the future.
The Consulting/Expert Industry
When you’ve got Generative AI (GPT’s) and AI agents do you need human consultants? That’s one question McKinsey is asking. According to one publication, The Finance Story, “McKinsey’s AI Agents replace 5000 consultants”. 12,000 new AI agents operate within the firm’s platform today (called Lilli - in place since 2023) and as such 25% of their projects are now outcome-based, meaning fees paid on outcomes, not hours. Doubtless, other consulting firms are taking the same approach. They are developing proprietary GenAI tools to interpret quantum research and translate it into business value propositions, aligning with Quantum Strategy Institute’s mission to bridge quantum tech and business outcomes.
So why not simply have organizations, large and small, create their own agents to do the former work of consultants? McKinsey offers that too. “McKinsey’s QuantumBlack Horizon (Created by QuantumBlack, AI) is transforming client industries with AI… McKinsey’s AI and machine learning platform that helps businesses rapidly develop, deploy, and scale AI solutions across their operations.”
Human Edge
The human edge is sometimes considered that of leadership, persuasion, and navigating office politics while humans still populate the office. In my experience, quantum tech is not widely understood today, and thus the expertise of human interpreters is critical. Constructing a quantum strategy has the same principles I’ve been talking about within Quantum’s Business substack and from the Quantum Strategy Institute for years. Only now AI has progressed to become a valuable time-reducing tool.
Analyzing vast datasets related to quantum computing applications, such as optimization, cryptography, and material science has its place, however the problem persists that the field is evolving so quickly that Gen AI platforms often only reference these latest updates when you direct them to rather than out of the gate. Generating actionable insights and simulating quantum-driven business scenarios still require human oversight (refer accuracy levels above). Consulting firms are training consultants to combine GenAI’s data-processing capabilities with quantum expertise, enabling faster and more precise strategic recommendations. Firms are also
Automating Routine Tasks to Focus on Quantum Innovation
GenAI automates time-intensive tasks like market research, trend analysis, and report generation, freeing consultants to focus on high-value activities such as designing quantum strategies or advising on quantum readiness. For instance, GenAI can draft reports on quantum export controls or summarize quantum computing advancements, allowing consultants to prioritize client-specific quantum use cases. Firms are investing in GenAI platforms to streamline internal processes, as seen with BCG’s deployment of over 3,000 GenAI tools for tasks like document summarization. In quantum consulting, this automation enables firms to stay current with rapid quantum advancements, ensuring they can quickly update clients on breakthroughs like quantum hardware improvements or algorithm developments.
Upskilling Consultants for AI-Quantum Synergy/”Experts”
The intersection of GenAI and quantum technology requires consultants to develop hybrid skills in data science, AI, and quantum computing. For example, consultants need to understand how GenAI can enhance quantum algorithm development or how quantum computing can accelerate GenAI training processes. This synergy is critical for advising clients on integrating both technologies for competitive advantage. One of the difficulties in following individual experts is the depth and breadth of their content and relating it to your own business problems. Experts may go deep (like certain PhD’s), they may go broad (like yours truly). Consulting firms are implementing training programs to equip consultants with AI and quantum literacy, often in collaboration with tech partners like IBM or OpenAI.
Competing with Tech Giants
The industry faces challenges from rising client expectations for data-driven insights, cost pressures, and competition from tech-native firms. Technology companies like OpenAI and IBM are entering the consulting space with hybrid AI-quantum offerings, challenging traditional firms. These companies leverage GenAI to provide quantum consulting services, such as advising on quantum algorithm integration or quantum cloud platforms. Consulting firms are differentiating themselves by combining GenAI with specialized quantum expertise, positioning themselves as strategic partners for quantum adoption.
Driving Client Engagement with Personalized Quantum Solutions
GenAI enables personalized client interactions by generating tailored content, such as quantum strategy roadmaps or industry-specific quantum use cases (e.g., quantum-enhanced AI for financial modeling). It also powers AI-driven chatbots or virtual assistants to engage clients in real-time, answering questions about quantum technology’s business implications. Firms are adopting GenAI-driven tools to customize client deliverables, attempting to ensure quantum strategies align with specific business goals. For example, consultants can use GenAI to create quantum-focused presentations that highlight tangible benefits, like cost reductions in logistics, drawing from Quantum Strategy Institute’s emphasis on practical quantum applications.
Navigating Ethical and Regulatory Challenges
GenAI’s use in quantum consulting raises ethical concerns, such as data privacy, algorithmic bias, and the accuracy of AI-generated quantum insights. Consultants must ensure GenAI outputs are validated by quantum experts to avoid “hallucinations” that could mislead clients about quantum capabilities. Additionally, quantum technology’s regulatory landscape (e.g., export controls) requires careful navigation, which GenAI can help analyze but must be human-verified. Firms are establishing robust governance frameworks to ensure responsible GenAI use, including regular audits for bias and compliance with quantum-related regulations. The Quantum Strategy Institute’s work on export controls highlights the need for consultants to use GenAI responsibly to provide accurate, compliant advice on quantum adoption.
Accelerating Quantum Adoption Through Thought Leadership
GenAI is used to create compelling thought leadership content, such as whitepapers or blogs on quantum computing’s business potential, helping consultants educate clients and attract interest. For example, GenAI can draft articles on quantum’s role in AI acceleration, aligning with that in my book *Quantum Boost* to demystify quantum for business leaders. Firms are leveraging GenAI to produce high-quality, SEO-optimized content at scale, positioning themselves as leaders in the quantum space. By sharing insights on platforms like LinkedIn, consultants can drive traffic to quantum-focused resources, such as quantumstrategyinstitute.com, to engage business leaders.
Preparing for Quantum-GenAI Convergence
The synergy between GenAI and quantum computing is an emerging frontier. Quantum computers could enhance GenAI’s capabilities by accelerating training of large language models, while GenAI can simulate quantum scenarios to guide business strategies. This convergence is critical for industries like finance and healthcare, where quantum-AI solutions could unlock significant value. Consulting firms are investing in R&D to explore quantum-GenAI integration, partnering with quantum tech providers to develop hybrid solutions. The Quantum Strategy Institute’s focus on tangible quantum benefits positions consultants to guide clients on adopting these converging technologies strategically.
Keeping Pace with Quantum Technology’s Rapid Evolution
The quantum technology landscape is advancing rapidly, with breakthroughs in quantum hardware, algorithms, and cloud platforms. Consulting firms are adapting to this pace by:
Continuous Learning: Using GenAI to monitor quantum research and summarize advancements, ensuring consultants stay informed about developments like the current status of efforts towards fault-tolerant quantum computing.
Strategic Partnerships: Collaborating with quantum tech firms to access cutting-edge tools and expertise, enabling consultants to offer up-to-date quantum strategies.
Client Education: Leveraging GenAI to create accessible content that demystifies quantum advancements, helping business leaders understand their strategic implications, as emphasized in my teams’ work at the Quantum Strategy Institute.
Summary
Quantum strategy is not being revolutionized rather its’ evolving with the power of AI. The consulting industry is adapting to GenAI by integrating it into core functions like data analysis, content creation, and client engagement, while addressing ethical and competitive challenges. In the context of quantum technology, GenAI empowers consultants to deliver quantum-focused strategies, automate routine tasks, and prepare clients for the quantum-AI convergence. By combining GenAI’s efficiency with specialized quantum expertise, akin to that championed by the Quantum Strategy Institute, consulting firms can guide business leaders through the fast-changing quantum landscape, striving to remain competitive and innovative.
Brian Lenahan is founder and chair of the Quantum Strategy Institute, author of seven Amazon published books on quantum technologies and artificial intelligence and a Substack Top 100 Rising in Technology. Brian’s focus on the practical side of technology ensures you will get the guidance and inspiration you need to gain value from quantum now and into the future. Brian does not purport to be an expert in each field or subfield for which he provides science communication.
Brian’s books are available on Amazon. Quantum Strategy for Business course is available on the QURECA platform.
Copyright © 2025 Aquitaine Innovation Advisors