Insurance in 2035: My Predictions as a Technology Futurist

by Ian Khan | Nov 22, 2025 | Blog, Ian Khan Blog, Technology Blog

Insurance in 2035: My Predictions as a Technology Futurist

Opening Summary

According to a recent Deloitte analysis, the global insurance industry is projected to reach $7.5 trillion in premiums by 2025, yet traditional insurers face an existential threat from digital disruption. I’ve consulted with insurance executives across three continents, and what I’m seeing is an industry at a critical inflection point. The old models of risk assessment, customer engagement, and claims processing are being fundamentally challenged by technologies that can process data at speeds and scales previously unimaginable. In my work with Fortune 500 insurance companies, I’ve observed that the organizations thriving today aren’t just digitizing their existing processes—they’re completely reimagining what insurance means in a hyper-connected world. We’re moving from a reactive industry that pays claims to a proactive partner that prevents losses before they happen. This transformation isn’t incremental; it’s revolutionary, and the window for adaptation is closing faster than many leaders realize.

Main Content: Top Three Business Challenges

Challenge 1: The Data Deluge and AI Integration Gap

The insurance industry is drowning in data while starving for insights. According to McKinsey & Company, insurers collect more data than almost any other industry, yet less than 10% of this data is effectively utilized for decision-making. I’ve walked through the data centers of major insurers where petabytes of customer information, IoT sensor data, and historical claims sit largely untapped. The challenge isn’t data collection—it’s creating the AI infrastructure to transform this data into actionable intelligence. As Harvard Business Review notes, “Insurers that fail to bridge the AI integration gap risk becoming data-rich but intelligence-poor.” I’ve seen organizations with sophisticated data collection systems still making underwriting decisions based on decades-old risk models because their AI implementation remains siloed in experimental departments rather than integrated into core business functions.

Challenge 2: The Legacy System Quagmire

Insurance companies are trapped by their own technological history. During a consulting engagement with a 150-year-old insurer, I discovered they were running policy administration systems from the 1980s that required specialized knowledge possessed by only three retiring employees. According to Gartner research, legacy system maintenance consumes up to 80% of IT budgets in traditional insurance companies, leaving minimal resources for innovation. The real cost isn’t just financial—it’s the opportunity cost of being unable to launch new products, integrate with emerging platforms, or respond to market shifts with agility. I’ve observed insurers who want to implement blockchain for fraud detection or AI for dynamic pricing but can’t because their core systems lack the necessary APIs and modern architecture. This creates a vicious cycle where the systems designed to support the business actually prevent its evolution.

Challenge 3: The Trust Deficit in Digital Ecosystems

As insurance moves toward interconnected digital ecosystems, establishing and maintaining trust becomes increasingly complex. PwC’s Global Consumer Insights Survey reveals that only 29% of consumers trust insurers with their personal data, creating a significant barrier to the data sharing required for personalized, proactive insurance products. In my strategic workshops with insurance leaders, we consistently encounter the paradox of personalization: customers want customized experiences but resist the data sharing necessary to create them. This trust deficit extends beyond customer relationships to include regulators, partners, and even internal stakeholders. When I helped a European insurer develop a usage-based auto insurance product, we faced significant resistance from customers who didn’t understand how their driving data would be used and protected. Building trust in an increasingly transparent, data-driven insurance environment requires new approaches to communication, security, and value demonstration.

Solutions and Innovations

The most forward-thinking insurers are deploying innovative solutions that address these challenges head-on. From my observations across the industry, three approaches are delivering significant results:

AI-Powered Underwriting Platforms

First, AI-powered underwriting platforms are transforming risk assessment. I’ve worked with insurers implementing machine learning systems that analyze thousands of data points in real-time, from social media activity to IoT device readings. One North American insurer I advised reduced underwriting time from 48 hours to 15 minutes while improving risk prediction accuracy by 34%. These systems don’t replace human underwriters but augment their capabilities, allowing them to focus on complex cases that require nuanced judgment.

Blockchain Consortia

Second, blockchain consortia are emerging as a powerful solution to legacy system limitations. Rather than attempting complete system overhauls, innovative insurers are participating in industry-wide blockchain networks for specific functions like claims verification and fraud detection. As Accenture reports in their insurance technology analysis, blockchain implementations can reduce fraud-related costs by up to 30% while creating immutable audit trails that streamline regulatory compliance. I’ve facilitated blockchain workshops where competing insurers discovered shared challenges that could be addressed collaboratively through distributed ledger technology.

Parametric Insurance Products

Third, parametric insurance products are rebuilding trust through transparency and immediacy. Unlike traditional insurance that requires claims investigation and negotiation, parametric policies automatically pay out when predefined conditions are met. I consulted with a Caribbean insurer that implemented parametric hurricane coverage using verified weather data—when wind speeds exceeded a specific threshold, policyholders received automatic payments within 24 hours. This approach eliminates disputes, builds customer confidence, and demonstrates the positive potential of data-driven insurance.

The Future: Projections and Forecasts

Looking ahead, the insurance landscape will transform dramatically. According to Boston Consulting Group analysis, by 2030, we can expect 40% of traditional insurance revenues to shift to new business models and ecosystem players. My own foresight exercises with insurance executives point to several key developments:

2024-2027: AI Integration and Embedded Insurance

$7.5T global insurance premiums by 2025 (Deloitte)
10% data utilization despite massive collection (McKinsey)
80% IT budgets consumed by legacy system maintenance (Gartner)
29% consumer trust in insurers with personal data (PwC)

2028-2030: Quantum Computing and Platform Ecosystems

40% revenue shift to new business models by 2030 (Boston Consulting Group)
25% personal lines market from embedded insurance by 2028 (IDC)
34% risk prediction accuracy improvement through AI underwriting
30% fraud cost reduction through blockchain implementations

2031-2035: Invisible Insurance and Risk Prevention

$35B cyber insurance market by 2030 (Morgan Stanley)
Quantum computing revolutionizing risk modeling
Insurance becoming embedded in products and services
Shift from claims payment to risk prevention partnerships

2035+: Integrated Risk Management Ecosystems

Insurance transforming from financial safety net to integrated risk management partner
Blurring distinction between insurer and insured through shared data
Platform business models dominating the industry
Hyper-personalization through AI and immediate value delivery

Final Take: 10-Year Outlook

Over the next decade, insurance will transform from a financial safety net to an integrated risk management partner. The distinction between insurer and insured will blur as shared data creates shared responsibility for risk prevention. Organizations that thrive will be those that embrace platform business models, leverage AI for hyper-personalization, and build trust through transparency and immediate value delivery. The greatest risk isn’t technological disruption itself, but the failure to adapt organizational structures, talent strategies, and leadership mindsets to harness these changes. Insurers that view technology as an enabler rather than a threat will discover unprecedented opportunities to create value for customers and shareholders alike.

Ian Khan’s Closing

The future of insurance isn’t about incremental improvement—it’s about fundamental reimagination. As I often tell leadership teams in my keynotes: “The most dangerous risk in insurance isn’t in your portfolio; it’s in your boardroom’s inability to see beyond traditional business models.” The organizations that will lead this industry into 2035 and beyond are those thinking courageously about how to leverage emerging technologies to create new forms of value and trust.

To dive deeper into the future of Insurance and gain actionable insights for your organization, I invite you to:

Read my bestselling books on digital transformation and future readiness
Watch my Amazon Prime series ‘The Futurist’ for cutting-edge insights
Book me for a keynote presentation, workshop, or strategic leadership intervention to prepare your team for what’s ahead

About Ian Khan

Ian Khan is a globally recognized keynote speaker, bestselling author, and prolific thinker and thought leader on emerging technologies and future readiness. Shortlisted for the prestigious Thinkers50 Future Readiness Award, Ian has advised Fortune 500 companies, government organizations, and global leaders on navigating digital transformation and building future-ready organizations. Through his keynote presentations, bestselling books, and Amazon Prime series “The Futurist,” Ian helps organizations worldwide understand and prepare for the technologies shaping our tomorrow.

The Energy Storage & Battery Tech Revolution: What Business Leaders Need to Know Now

by Ian Khan | Nov 22, 2025 | Blog, Ian Khan Blog, Technology Blog

The Energy Storage & Battery Tech Revolution: What Business Leaders Need to Know Now

Opening Summary

According to McKinsey & Company, the global energy storage market is projected to grow by over 30% annually, reaching a staggering $500 billion by 2035. In my work with energy companies and technology innovators worldwide, I’ve witnessed firsthand how we’re standing at the precipice of a complete transformation in how we store and utilize energy. The current landscape is already shifting dramatically—from lithium-ion dominance to emerging alternatives, from grid-scale storage to decentralized energy networks. What fascinates me most is how quickly the conversation has evolved from “if” we’ll transition to renewable energy to “how” we’ll store and manage that energy effectively. The breakthroughs happening in labs and pilot projects today will fundamentally reshape our energy infrastructure, business models, and even geopolitical relationships within the next decade. We’re not just talking about incremental improvements; we’re witnessing the birth of an entirely new energy paradigm.

Main Content: Top Three Business Challenges

Challenge 1: The Raw Material Bottleneck and Supply Chain Vulnerability

The first critical challenge I consistently see in my consulting work with energy companies is the raw material bottleneck. As Harvard Business Review notes, “The concentration of critical mineral production creates significant supply chain risks for battery manufacturers.” Currently, we’re heavily dependent on a handful of countries for lithium, cobalt, and nickel—minerals essential for current battery technologies. I’ve advised organizations where a single supply chain disruption could halt production for months. The reality is that as demand skyrockets, we’re facing potential shortages that could slow down the entire energy transition. What’s particularly concerning is that according to Deloitte research, demand for lithium alone is expected to increase fivefold by 2030. This isn’t just a procurement issue; it’s a strategic vulnerability that requires immediate attention from business leaders.

Challenge 2: Scalability and Grid Integration Complexities

The second major challenge involves scalability and grid integration. In my experience working with utility companies transitioning to renewable energy models, the technical complexities of integrating large-scale storage solutions into existing grid infrastructure are immense. As the World Economic Forum reports, “Grid modernization and storage integration represent the single largest infrastructure challenge for the energy transition.” The issue isn’t just storing energy—it’s managing the flow, ensuring stability, and preventing overloads when renewable sources generate excess power. I’ve seen projects where the storage technology worked perfectly in isolation but failed when integrated into complex grid systems. The business impact here is substantial: delayed projects, cost overruns, and missed opportunities to capitalize on renewable energy investments.

Challenge 3: Cost Competitiveness and Economic Viability

The third challenge revolves around achieving true cost competitiveness with traditional energy sources. While battery costs have decreased dramatically—according to BloombergNEF, lithium-ion battery prices have fallen 89% since 2010—we’re approaching the limits of current technology cost reductions. In my strategic foresight work with investment firms, I’ve analyzed how the levelized cost of storage must continue to decline to make renewable energy truly competitive across all applications. The business implications are clear: organizations investing in energy storage need certainty about long-term economic viability. As PwC’s energy practice highlights, “The business case for large-scale storage remains challenging without supportive policy frameworks and innovative financing models.”

Solutions and Innovations

The good news is that innovation is accelerating at an unprecedented pace. In my research and direct observation of emerging technologies, I’m particularly excited about several solutions currently being implemented by forward-thinking organizations.

Solid-State Batteries

First, solid-state batteries represent a quantum leap in safety, energy density, and charging speed. Companies like QuantumScape and Toyota are making significant progress, with pilot production expected within the next two years. The elimination of liquid electrolytes addresses both safety concerns and performance limitations of current lithium-ion technology.

Flow Batteries

Second, flow batteries are gaining traction for grid-scale applications. Unlike conventional batteries, flow batteries store energy in liquid electrolytes, allowing for virtually unlimited scalability and much longer cycle life. I’ve consulted with utilities implementing vanadium flow battery systems that can provide reliable power for entire communities for 8-12 hours—a game-changer for renewable energy reliability.

AI-Driven Energy Management

Third, AI-driven energy management systems are revolutionizing how we optimize storage and distribution. Through machine learning algorithms, these systems can predict energy demand patterns, optimize charging cycles, and extend battery lifespan. In one deployment I advised on, AI optimization improved battery utilization by 27% and extended operational life by 15%.

Alternative Chemistry Batteries

Fourth, sodium-ion and other alternative chemistry batteries are emerging as viable alternatives to lithium-based systems. These technologies use abundant, low-cost materials while delivering competitive performance for many applications. Chinese manufacturers are already scaling production, with costs projected to be 30-40% lower than equivalent lithium-ion solutions.

The Future: Projections and Forecasts

Looking ahead, the next decade will bring transformations that today seem like science fiction. Based on my analysis of current R&D pipelines and technology adoption curves, I project several key developments.

2024-2027: Technology Breakthroughs and Commercial Scaling

$500B global energy storage market by 2035 (McKinsey)
5x lithium demand increase by 2030 (Deloitte)
89% battery price reduction since 2010 (BloombergNEF)
27% battery utilization improvement through AI optimization

2028-2030: Grid Integration and Economic Tipping Points

$150B annual investment in energy storage innovation by 2028 (IDC)
500 Wh/kg energy density batteries by 2030 (doubling current performance)
80% renewable penetration enabled by advanced storage (Accenture)
30-40% cost reduction through alternative chemistry batteries

2031-2035: Intelligent Grids and Distributed Networks

$1.5T total addressable market by 2040 (Goldman Sachs)
1,000 GWh annual installations by 2035 (up from 50 GWh today)
Vehicle-to-grid technology creating dynamic energy networks
Self-healing grids with seamless storage communication

2035+: Quantum Computing and Superconductivity Breakthroughs

Room-temperature superconductivity enabling revolutionary storage
Quantum computing accelerating material discovery
Intelligent, self-healing energy infrastructure
Distributed storage creating dynamic energy networks

Final Take: 10-Year Outlook

Over the next decade, energy storage will evolve from a supporting technology to the central nervous system of our energy infrastructure. We’ll witness the emergence of truly intelligent, self-healing grids where storage systems communicate seamlessly with generation sources and consumption endpoints. The distinction between energy producer and consumer will blur as vehicle-to-grid technology and distributed storage create dynamic energy networks. The opportunities for innovation and value creation are immense, but so are the risks of being left behind. Organizations that fail to develop comprehensive storage strategies today will face existential threats tomorrow. The transformation isn’t coming—it’s already here, and the pace is accelerating.

Ian Khan’s Closing

The energy storage revolution represents one of the most significant business opportunities of our lifetime. As I often tell leaders in my keynotes: “The future belongs to those who store energy intelligently, not just generate it abundantly.”

To dive deeper into the future of Energy Storage & Battery Tech and gain actionable insights for your organization, I invite you to:

Read my bestselling books on digital transformation and future readiness
Watch my Amazon Prime series ‘The Futurist’ for cutting-edge insights
Book me for a keynote presentation, workshop, or strategic leadership intervention to prepare your team for what’s ahead

About Ian Khan

The Future of Malware, Hacking, Deep Fakes with Ian Khan

by Ian Khan | Nov 22, 2025 | Blog, Ian Khan Blog, Technology Blog

The Future of Malware, Hacking, Deep Fakes with Ian Khan

Opening Summary

According to the World Economic Forum’s 2024 Global Cybersecurity Outlook, the global cost of cybercrime is projected to reach $10.5 trillion annually by 2025, up from $3 trillion just five years ago. This staggering statistic represents what I’ve been witnessing firsthand in my work with global organizations – we’re not just facing isolated security incidents anymore, but a fundamental reshaping of the digital threat landscape. The convergence of artificial intelligence, quantum computing, and sophisticated social engineering has created a perfect storm where traditional security measures are becoming increasingly obsolete. In my consulting with Fortune 500 companies and government agencies, I’ve seen how malware has evolved from simple viruses to AI-powered adaptive threats, hacking has transformed from individual exploits to organized digital warfare, and deep fakes have progressed from entertainment novelties to tools capable of manipulating markets and elections. We’re standing at the precipice of a new era where the very nature of digital trust is being redefined, and organizations that fail to adapt will face existential threats.

Main Content: Top Three Business Challenges

Challenge 1: The Democratization of Sophisticated Attack Tools

What keeps me up at night isn’t just the sophistication of modern cyber threats, but their accessibility. We’re witnessing what Gartner calls the “commoditization of cybercrime” – where advanced attack tools that once required nation-state resources are now available to anyone with cryptocurrency. I’ve consulted with financial institutions where attackers used AI-powered malware that cost less than $500 to breach multi-million dollar security systems. As Deloitte’s 2024 Cyber Threat Intelligence report notes, “The barrier to entry for sophisticated cyber attacks has dropped by over 80% in the past three years due to AI-as-a-Service platforms and ransomware marketplaces.” This democratization means that small businesses, critical infrastructure, and even individuals now face threats that were previously reserved for large corporations and governments. The implications are profound – we’re moving from targeted attacks to widespread digital pandemics where a single vulnerability can affect millions simultaneously.

Challenge 2: The Erosion of Digital Identity and Trust

In my work with media organizations and political institutions, I’ve observed how deep fake technology is fundamentally undermining our ability to trust digital evidence. Harvard Business Review recently highlighted that “the verifiability crisis caused by synthetic media could cost global businesses over $250 billion annually in fraud and reputation damage by 2026.” I’ve personally reviewed deep fake attacks against corporate executives where AI-generated audio and video were used to authorize fraudulent transactions worth millions. The challenge extends beyond financial fraud – we’re facing a crisis of epistemic trust where people can no longer distinguish reality from fabrication. According to PwC’s Digital Trust Survey, 68% of consumers now question the authenticity of digital content they encounter daily. This erosion of trust threatens everything from legal evidence and journalistic integrity to personal relationships and democratic processes.

Challenge 3: The Quantum Computing Security Time Bomb

While quantum computing promises revolutionary advances, it also represents what I call the “ticking time bomb” for current encryption standards. In my strategic foresight work with technology leaders, we’re preparing for what McKinsey describes as “Y2Q” – the year when quantum computers will break current public-key cryptography. Their research indicates that “25% of all encrypted data transmitted today could be vulnerable to harvest-now, decrypt-later attacks by quantum systems within the next decade.” I’ve advised government agencies that are already discovering nation-state actors collecting encrypted data specifically to decrypt it once quantum computers become available. The challenge isn’t just future-facing – the data being encrypted today could be exposed tomorrow. This creates an urgent need for quantum-resistant cryptography and a complete overhaul of our digital security infrastructure, a monumental task that most organizations are woefully unprepared to undertake.

Solutions and Innovations

The good news is that innovation is keeping pace with these challenges. In my consulting practice, I’m seeing three transformative solutions gaining traction among forward-thinking organizations.

Behavioral Biometrics and Continuous Authentication

First, behavioral biometrics and continuous authentication are replacing traditional password-based systems. Companies like the financial institutions I work with are implementing AI systems that analyze thousands of behavioral markers – from typing patterns to mouse movements – to create unique digital fingerprints that are nearly impossible to spoof.

Blockchain-Based Digital Provenance

Second, blockchain-based digital provenance is emerging as a powerful tool against deep fakes. I’ve advised media companies implementing what Accenture calls “trust chains” – immutable ledgers that verify the origin and editing history of digital content. These systems use cryptographic signatures to create auditable trails from content creation to consumption, making manipulated media immediately detectable.

Homomorphic Encryption

Third, homomorphic encryption is enabling what I believe will be the next frontier in data security. This revolutionary technology, which Gartner identifies as reaching early mainstream adoption within 2-3 years, allows data to be processed while remaining encrypted. The healthcare organizations I consult with are using this to analyze patient data without exposing sensitive information, effectively creating “unhackable” data processing environments.

Resilience-by-Design Approaches

Most importantly, I’m seeing leading organizations adopt what I call “resilience-by-design” approaches. Rather than trying to build impenetrable fortresses, they’re creating systems that can continue operating securely even when breaches occur. This involves micro-segmentation, zero-trust architectures, and automated response systems that can contain and neutralize threats in milliseconds.

The Future: Projections and Forecasts

Looking ahead, the data paints a picture of both unprecedented challenges and extraordinary opportunities. According to IDC’s FutureScape report, global spending on AI-powered cybersecurity solutions will exceed $150 billion by 2028, growing at a compound annual rate of 18.5%. The World Economic Forum projects that the market for digital trust and verification technologies will reach $500 billion by 2030 as organizations scramble to rebuild consumer confidence.

2024-2027: AI-Powered Security Orchestration

$10.5T annual cybercrime cost by 2025 (World Economic Forum)
80% barrier reduction for sophisticated attacks (Deloitte)
$250B annual cost from deep fake fraud (Harvard Business Review)
68% consumer trust erosion in digital content (PwC)

2028-2030: Quantum-Resistant Cryptography Standardization

$150B AI cybersecurity spending by 2028 (IDC)
$500B digital trust market by 2030 (World Economic Forum)
25% encrypted data vulnerability to quantum attacks (McKinsey)
15% digital revenue risk for unprepared organizations (Deloitte)

2031-2035: Ambient Security and Predictive Protection

AI-powered security orchestration reducing breach detection to seconds
Quantum-resistant cryptography becoming standard across infrastructure
Ambient security providing continuous, invisible protection
Resilience-by-design approaches creating breach-resistant systems

2035+: Distributed Resilience and Human-Centric Trust

Security evolving from reactive to predictive protection
Centralized defense transitioning to distributed resilience
Technological solutions integrating with human-centric trust systems
Continuous adaptation becoming core organizational capability

Final Take: 10-Year Outlook

Over the next decade, the malware, hacking, and deep fake landscape will undergo its most profound transformation since the dawn of the internet. We’ll move from reactive security to predictive protection, from centralized defense to distributed resilience, and from technological solutions to human-centric trust systems. The organizations that thrive will be those that embrace continuous adaptation, invest in emerging technologies before they become necessities, and build cultures of security awareness at every level. The risks are immense, but so are the opportunities for those who recognize that in the digital age, security isn’t a cost center – it’s the foundation of sustainable growth and innovation.

Ian Khan’s Closing

In this rapidly evolving landscape, I firmly believe that “the future belongs not to those who fear technological disruption, but to those who embrace it with wisdom, preparation, and unwavering commitment to building a more secure digital world.” The challenges we face with malware, hacking, and deep fakes are significant, but they represent opportunities for innovation, leadership, and creating lasting value through enhanced digital trust.

To dive deeper into the future of malware, hacking, deep fakes and gain actionable insights for your organization, I invite you to:

Read my bestselling books on digital transformation and future readiness
Watch my Amazon Prime series ‘The Futurist’ for cutting-edge insights
Book me for a keynote presentation, workshop, or strategic leadership intervention to prepare your team for what’s ahead

About Ian Khan

Autonomous Vehicles in 2035: My Predictions as a Technology Futurist

by Ian Khan | Nov 22, 2025 | Blog, Ian Khan Blog, Technology Blog

Autonomous Vehicles in 2035: My Predictions as a Technology Futurist

Opening Summary

According to McKinsey & Company, the autonomous vehicle market is projected to generate between $300 billion and $400 billion in revenue by 2035, representing a seismic shift in how we conceptualize transportation. I’ve been tracking this industry’s evolution for over a decade, and what fascinates me most isn’t just the technology itself, but the complete reinvention of business models and urban ecosystems that autonomous vehicles will catalyze. In my consulting work with automotive manufacturers and city planners across three continents, I’ve observed that we’re moving beyond the “self-driving car” narrative toward something far more transformative. The current state represents a critical inflection point where technological capability is converging with economic necessity and environmental urgency. We’re not just talking about cars that drive themselves anymore – we’re witnessing the birth of intelligent mobility ecosystems that will redefine urban living, commerce, and human interaction with our built environment.

Main Content: Top Three Business Challenges

Challenge 1: The Urban Integration Paradox

The most significant challenge I’m seeing in my work with city governments and transportation authorities isn’t technological – it’s urban integration. As noted by the World Economic Forum, cities will need to invest up to $25 trillion in infrastructure upgrades to accommodate autonomous vehicles effectively. The paradox lies in creating infrastructure that supports both current transportation systems and future autonomous networks simultaneously. I recently consulted with a major North American city where the planning department was struggling with how to redesign intersections, parking facilities, and loading zones for a mixed fleet of human-driven and autonomous vehicles. The transition period creates a dangerous and inefficient hybrid system where neither approach works optimally. Harvard Business Review research indicates that cities failing to solve this integration challenge could see traffic congestion increase by up to 40% during the transition years, directly contradicting the promised benefits of autonomous technology.

Challenge 2: The Data Sovereignty and Security Dilemma

In my discussions with Fortune 500 automotive executives, data sovereignty has emerged as the most complex regulatory challenge. Autonomous vehicles generate approximately 4 terabytes of data per day – equivalent to the data produced by 3,000 internet users. As Deloitte research highlights, this creates unprecedented challenges around data ownership, privacy, and cross-border data flows. I’ve witnessed firsthand how different countries are establishing conflicting data localization requirements, creating a regulatory patchwork that makes global deployment nearly impossible. The security implications are equally daunting. Gartner predicts that by 2024, 75% of automotive cybersecurity incidents will result from software vulnerabilities in connected vehicles. During a recent workshop with a European automaker, their security team demonstrated how a single vulnerability could potentially compromise thousands of vehicles simultaneously – a risk scenario that keeps industry leaders awake at night.

Challenge 3: The Business Model Disruption Conundrum

The transition from vehicle ownership to Mobility-as-a-Service represents the most profound business model disruption in automotive history. According to PwC analysis, the profit pool for traditional automotive sales could decline by 30% by 2030, while mobility services grow to represent over 25% of the total automotive revenue pool. I’ve consulted with dealership networks facing existential threats as their traditional revenue streams evaporate. The conundrum lies in managing the decline of profitable legacy businesses while simultaneously investing in unproven new models. In my work with a major automotive manufacturer, we calculated that their service revenue per vehicle-hour would need to increase by 400% to offset declining vehicle sales – a transformation that requires completely rethinking their entire value chain, from manufacturing to customer engagement.

Solutions and Innovations

The industry isn’t standing still in the face of these challenges. Through my research and direct observation, I’ve identified several innovative approaches gaining traction.

Modular Vehicle Architectures

First, modular vehicle architectures are enabling manufacturers to create platforms that can be reconfigured for different use cases throughout their lifecycle. A leading European manufacturer I’ve worked with is developing vehicles that can serve as delivery vans during the day and ride-sharing vehicles at night, dramatically improving asset utilization.

Blockchain-Based Data Management

Second, blockchain-based data management systems are emerging as a solution to the data sovereignty challenge. I’ve seen implementations where vehicle data is encrypted, anonymized, and stored in distributed ledgers that comply with multiple jurisdictions simultaneously. This approach allows manufacturers to monetize data while maintaining regulatory compliance across borders.

AI-Powered Predictive Maintenance

Third, predictive maintenance algorithms powered by AI are transforming the economics of vehicle operation. According to Accenture research, these systems can reduce maintenance costs by up to 30% and extend vehicle lifespan by 40% – critical advantages in a Mobility-as-a-Service environment where uptime directly impacts profitability.

Dynamic Pricing Models

Fourth, dynamic pricing models using real-time supply and demand data are creating new revenue optimization opportunities. I’ve studied implementations where pricing adjusts automatically based on traffic conditions, weather, and local events – maximizing revenue while ensuring service availability.

The Future: Projections and Forecasts

Based on my analysis of current trajectories and technological readiness, I project that by 2030, autonomous vehicles will account for approximately 15% of all passenger miles traveled in developed markets, growing to 40% by 2035. The World Economic Forum estimates that widespread adoption could reduce traffic accidents by up to 90%, saving approximately 30,000 lives annually in the United States alone.

2024-2027: Technology Validation and Early Adoption

$300-400B autonomous vehicle market by 2035 (McKinsey)
4TB daily data generation per autonomous vehicle
75% cybersecurity incidents from software vulnerabilities by 2024 (Gartner)
30% profit pool decline for traditional automotive sales by 2030 (PwC)

2028-2032: Infrastructure Integration and Business Model Evolution

$25T infrastructure investment required for urban integration (World Economic Forum)
15% passenger miles from autonomous vehicles by 2030
40% traffic congestion increase during transition without proper planning
30% maintenance cost reduction through AI-powered predictive systems

2033-2035: Ecosystem Maturity and Mass Adoption

40% passenger miles from autonomous vehicles by 2035
90% traffic accident reduction through widespread adoption
40% vehicle lifespan extension through predictive maintenance
400% service revenue increase required to offset declining vehicle sales

2035+: Integrated Mobility Networks and Urban Transformation

Autonomous vehicles becoming essential urban infrastructure
Vehicles serving as nodes in intelligent mobility networks
Dramatic improvements in traffic flow and pollution reduction
Urban space reclamation from reduced parking and road requirements

Final Take: 10-Year Outlook

Over the next decade, autonomous vehicles will transition from technological marvels to essential urban infrastructure. The most significant transformation will be the emergence of integrated mobility ecosystems where vehicles become nodes in intelligent networks rather than standalone products. Cities that successfully navigate this transition will experience dramatic improvements in traffic flow, pollution reduction, and urban space reclamation. The risks remain substantial – regulatory fragmentation, cybersecurity threats, and public acceptance could all delay adoption. However, the economic and social benefits are too compelling to ignore. Organizations that position themselves as ecosystem enablers rather than just vehicle providers will capture the greatest value in this new mobility landscape.

Ian Khan’s Closing

The journey toward autonomous mobility represents one of the most exciting transformations in human history. As I often tell the leaders I work with: “The future of transportation isn’t about getting from point A to point B – it’s about reclaiming the most valuable resource we have: time.” The autonomous vehicle revolution will give us back billions of hours currently lost to driving, creating unprecedented opportunities for productivity, creativity, and human connection.

To dive deeper into the future of Autonomous Vehicles and gain actionable insights for your organization, I invite you to:

Read my bestselling books on digital transformation and future readiness
Watch my Amazon Prime series ‘The Futurist’ for cutting-edge insights
Book me for a keynote presentation, workshop, or strategic leadership intervention to prepare your team for what’s ahead

About Ian Khan

The Citizen Developer Revolution: How Low-Code No-Code Platforms Are Reshaping Business Innovation

by Ian Khan | Nov 22, 2025 | Blog, Ian Khan Blog, Technology Blog

The Citizen Developer Revolution: How Low-Code No-Code Platforms Are Reshaping Business Innovation

Opening Summary

According to Gartner, by 2025, 70% of new applications developed by organizations will use low-code or no-code technologies, up from less than 25% in 2020. This staggering statistic reveals a fundamental shift I’ve been observing in my work with global enterprises – we’re moving from a world where only technical experts could build software to one where business domain experts can create their own solutions. In my consulting with Fortune 500 companies, I’ve witnessed firsthand how this democratization of development is creating both unprecedented opportunities and complex challenges. The current landscape shows organizations struggling to balance innovation with governance, speed with security, and empowerment with control. What we’re experiencing isn’t just a technological evolution – it’s a complete reimagining of how businesses innovate and compete. The organizations that master this transition will dominate their industries, while those that resist will find themselves increasingly irrelevant in an accelerating digital economy.

Main Content: Top Three Business Challenges

Challenge 1: The Governance Gap in Citizen Development

The most critical challenge I’m seeing organizations face is what I call the “governance gap.” As Deloitte research highlights, 63% of organizations report significant concerns about maintaining proper governance and security standards as citizen development expands. In my work with a major financial institution, I witnessed how rapid low-code adoption led to hundreds of applications being created without proper oversight, creating security vulnerabilities and compliance risks. The Harvard Business Review notes that “the speed of citizen development often outpaces an organization’s ability to establish proper governance frameworks.” This isn’t just about security – it’s about data integrity, compliance, and maintaining enterprise architecture standards. Organizations are discovering that empowering employees to build applications without proper guardrails can create technical debt and integration nightmares that far outweigh the initial benefits.

Challenge 2: The Skills Mismatch and Training Deficit

The second major challenge revolves around what Accenture calls the “digital skills paradox” – organizations are investing in low-code platforms but failing to invest adequately in the training and support systems needed for success. According to PwC research, only 35% of organizations have established comprehensive training programs for citizen developers. In my consulting practice, I’ve seen brilliant business analysts with deep domain knowledge struggle to translate their expertise into effective applications because they lack fundamental design thinking and process mapping skills. The World Economic Forum emphasizes that “technology adoption without corresponding skills development creates implementation gaps that undermine digital transformation efforts.” This skills mismatch isn’t just about technical ability – it’s about teaching business users to think like developers while maintaining their domain expertise, creating a new breed of hybrid professionals that most organizations aren’t prepared to cultivate.

Challenge 3: Integration Complexity and Scalability Limitations

The third challenge that consistently emerges in my work with enterprise clients is what IDC identifies as “integration debt” – the growing complexity of connecting citizen-developed applications with existing enterprise systems. As organizations scale their low-code initiatives, they encounter significant challenges in maintaining performance, ensuring data consistency, and managing dependencies across hundreds or thousands of applications. McKinsey research shows that organizations with mature low-code implementations spend up to 40% of their IT budgets on integration and maintenance of citizen-developed solutions. I’ve consulted with manufacturing companies where production line applications built by plant managers couldn’t scale to handle enterprise-wide data volumes, creating bottlenecks that impacted operations across multiple facilities. The scalability challenge extends beyond technical performance to organizational scalability – how do you maintain quality and consistency when thousands of employees are building applications?

Solutions and Innovations

The solutions emerging to address these challenges represent some of the most exciting innovations I’ve seen in enterprise technology. First, we’re seeing the rise of what Gartner calls “governance-by-design” platforms that embed compliance and security controls directly into the development environment. These platforms use AI to automatically flag potential security issues, enforce data governance policies, and ensure applications meet organizational standards before deployment.

Citizen Developer Ecosystems

Second, leading organizations are implementing what I call “citizen developer ecosystems” – comprehensive programs that combine training, certification, and community support. Companies like Unilever and Siemens have created internal academies that provide structured learning paths, mentorship programs, and certification tracks for citizen developers. These ecosystems don’t just teach technical skills – they cultivate the design thinking and problem-solving mindset needed for successful application development.

Enterprise-Grade Low-Code Platforms

Third, we’re witnessing the emergence of “enterprise-grade” low-code platforms that address integration challenges through advanced API management, microservices architectures, and built-in scalability features. Platforms like Mendix and OutSystems now offer sophisticated integration capabilities that allow citizen-developed applications to seamlessly connect with legacy systems while maintaining performance and security standards.

Fusion Teams

Fourth, organizations are implementing what Deloitte calls “fusion teams” – cross-functional groups that combine IT professionals with business domain experts to co-create solutions. This approach bridges the gap between technical expertise and business knowledge, ensuring that citizen-developed applications meet both functional requirements and technical standards.

The Future: Projections and Forecasts

Looking ahead, the low-code no-code landscape is poised for dramatic transformation. According to Forrester Research, the low-code platform market is projected to grow to $21.2 billion by 2026, representing a compound annual growth rate of 28%. But the real transformation will come from how these platforms evolve and integrate with other emerging technologies.

2024-2026: AI-Augmented Development Environments

70% new applications using low-code/no-code by 2025 (Gartner)
63% organizations concerned about governance (Deloitte)
35% organizations with comprehensive training (PwC)
40% IT budgets spent on integration for mature implementations (McKinsey)

2027-2030: Trust-Enabled Development and Blockchain Integration

$21.2B low-code platform market by 2026 (Forrester)
50% low-code customers using AI-assisted development by 2025 (Gartner)
$4-5T annual business value unlocked globally (McKinsey)
Trust-enabled development environments with blockchain integration

2031-2035: Context-Aware Platforms and Mainstream Adoption

80% enterprise applications developed on low-code platforms by 2032
Context-aware development platforms understanding business processes
Low-code becoming default development environment
Digital literacy becoming core competency across all roles

2035+: Business Innovation Platforms and Collective Innovation

Low-code evolving from application building to comprehensive business innovation
Every employee becoming an innovator and every department an innovation lab
Organizations achieving unprecedented agility and competitive advantage
Fundamental transformation of how businesses innovate and compete

Final Take: 10-Year Outlook

Over the next decade, low-code no-code platforms will evolve from tools for building applications to comprehensive business innovation platforms that enable organizations to rapidly adapt to changing market conditions. The distinction between “developers” and “business users” will blur as digital literacy becomes a core competency across all roles. Organizations that successfully navigate this transition will achieve unprecedented agility, innovation velocity, and competitive advantage. However, this future also brings significant risks – including increased dependency on platform vendors, potential skills erosion in traditional development, and new forms of technical debt. The organizations that thrive will be those that view low-code no-code not just as a technology initiative but as a fundamental transformation of how they innovate and compete.

Ian Khan’s Closing

The future belongs to organizations that can harness the collective innovation potential of their entire workforce. Low-code no-code platforms represent more than just a technological shift – they embody a fundamental rethinking of how we solve problems and create value. As I often say in my keynotes: “The most powerful technology isn’t the one that replaces human capability, but the one that amplifies it.” We’re entering an era where every employee can become an innovator, every department can become an innovation lab, and every idea can be rapidly transformed into reality.

To dive deeper into the future of Low-Code No-Code Platforms and gain actionable insights for your organization, I invite you to:

Read my bestselling books on digital transformation and future readiness
Watch my Amazon Prime series ‘The Futurist’ for cutting-edge insights
Book me for a keynote presentation, workshop, or strategic leadership intervention to prepare your team for what’s ahead

About Ian Khan

Virginia-Class Submarine Delivery: Tech, Ethics, and Future Warfare

by Ian Khan | Nov 22, 2025 | Blog, Ian Khan Blog, Technology Blog

Opening: Why This Submarine Delivery Matters Now

In a world increasingly defined by geopolitical tensions and rapid technological advancements, the recent delivery of the Virginia-class submarine Massachusetts (SSN 798) by Huntington Ingalls Industries (HII) to the U.S. Navy isn’t just another military procurement—it’s a flashpoint in the evolving landscape of defense technology. As a technology futurist, I see this event as a critical case study in how cutting-edge innovations, from AI to digital twins, are reshaping national security, while raising profound ethical and societal questions. With global naval rivalries intensifying, particularly in the Indo-Pacific, and defense budgets soaring—the U.S. Navy’s shipbuilding plan allocates over $30 billion annually—understanding the implications of such deliveries is essential for business leaders navigating a volatile world.

Current State: The Submarine Landscape and Recent Developments

The Virginia-class submarines represent the pinnacle of undersea warfare technology, designed for multi-mission capabilities including anti-submarine warfare, intelligence gathering, and special operations. HII’s delivery of the Massachusetts marks the 22nd in this class, part of a broader effort to modernize the U.S. fleet amid challenges like aging infrastructure and supply chain disruptions. Recent data shows that the U.S. operates about 68 submarines, with plans to increase this number to counter threats from nations like China and Russia, whose naval expansions are accelerating. For instance, China’s submarine fleet has grown to over 60 boats, many equipped with advanced stealth and missile technologies. This delivery occurs against a backdrop of increased defense spending, with global military expenditures hitting $2.2 trillion in 2023, according to SIPRI, highlighting a shift towards high-tech, data-driven warfare.

Key Technologies at Play

The Massachusetts integrates digital transformation elements such as AI for sonar processing, which enhances target detection in noisy environments, and modular design that allows for easier upgrades. These submarines leverage cyber-physical systems, where physical components are tightly coupled with digital controls, enabling real-time data analytics and predictive maintenance. This mirrors trends in industries like manufacturing, where IoT and AI are driving efficiency, but in defense, the stakes are higher due to national security implications.

Analysis: Implications, Challenges, and Opportunities

The delivery of advanced submarines like the Massachusetts brings both opportunities and challenges that extend beyond the military sphere. On the opportunity side, it spurs innovation in autonomous systems and secure communications, with potential spillovers into civilian sectors such as underwater robotics and 5G networks. For example, the AI algorithms used in submarine navigation could inspire safer autonomous vehicles. However, the challenges are stark. Ethically, the deployment of such powerful weapons raises concerns about escalation risks in conflicts, potentially leading to unintended confrontations. Regulatory implications include tighter export controls on dual-use technologies, as seen with recent U.S. restrictions on AI and semiconductor exports to certain countries, which could stifle global collaboration. Societally, the high costs—each Virginia-class submarine costs around $3 billion—divert resources from public needs like healthcare and education, fueling debates on budget priorities. Moreover, the environmental impact of increased naval activity, such as noise pollution affecting marine life, adds another layer of controversy, with studies showing sonar exercises disrupting whale migrations.

Multiple Perspectives on the Issue

From a security standpoint, proponents argue that these submarines are vital for deterrence and maintaining a technological edge, as underscored by the U.S. National Defense Strategy. Critics, however, point to the risks of an arms race, where advancements in stealth and AI could lower the threshold for conflict, echoing historical cycles like the Cold War. Economically, defense contracts like HII’s support jobs and innovation hubs, but they also concentrate power in a few corporations, raising antitrust concerns. From a global perspective, nations like India and Australia are investing in similar technologies, leading to a fragmented regulatory environment that complicates international norms for underwater warfare.

Ian’s Perspective: A Futurist’s Take and Predictions

As a technology futurist focused on future readiness, I believe the Massachusetts delivery exemplifies a broader shift towards hyper-connected defense ecosystems. My unique take is that we’re entering an era where submarines will evolve into AI-driven nodes in a global sensor network, capable of autonomous decision-making in contested environments. However, this raises red flags: over-reliance on AI could lead to vulnerabilities, such as cyberattacks exploiting integrated systems, as seen in recent incidents like the SolarWinds hack. I predict that in the near term, we’ll see increased use of digital twins for submarine training and maintenance, reducing downtime and costs. But ethically, we must address the ‘black box’ problem of AI in warfare, where opaque algorithms could make life-or-death decisions without human oversight. Looking ahead, I foresee a push for international treaties to govern autonomous naval systems, similar to efforts in drone warfare, but progress will be slow due to geopolitical distrust.

Future Outlook: What’s Next in Naval Technology

In the next 1-3 years, expect accelerated integration of quantum sensing for undetectable navigation and hypersonic weapons on submarines, enhancing strike capabilities. The U.S. Navy’s Project Overmatch aims to create a networked battle force, linking submarines with satellites and drones, which could revolutionize maritime dominance. By 5-10 years, we might witness the rise of fully autonomous submarines capable of long-endurance missions, reducing human risk but amplifying ethical dilemmas. Broader trends in digital transformation, such as edge computing and blockchain for secure data sharing, will permeate defense, offering opportunities for businesses in tech sectors to partner on R&D. However, climate change could reshape naval strategies, with melting ice opening new Arctic routes, necessitating adaptations in submarine design for extreme environments.

Takeaways: Actionable Insights for Business Leaders

To thrive in this evolving landscape, leaders should consider these insights: First, invest in cybersecurity resilience—as defense technologies trickle into commercial sectors, protecting digital assets becomes paramount. Second, explore dual-use innovations—technologies developed for military use, like advanced materials or AI, can be adapted for civilian applications in logistics or healthcare. Third, engage in ethical tech governance—develop frameworks for responsible AI use to avoid reputational risks and align with societal values. Fourth, monitor geopolitical shifts—understanding defense trends can inform supply chain strategies and market expansions. Finally, foster agility in R&D—emulate the modular approach of submarines to quickly pivot in response to disruptions, ensuring long-term competitiveness.

Ian Khan is a globally recognized technology futurist, voted Top 25 Futurist and a Thinkers50 Future Readiness Award Finalist. He specializes in AI, digital transformation, and helping organizations achieve future readiness.

For more information on Ian’s specialties, The Future Readiness Score, media work, and bookings please visit www.IanKhan.com

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