Artificial intelligence will change our experience of “applications” and “software” much as cloud computing changed the way people use apps and software. Perhaps nothing about AI experiences will change so much as deliberate actions on our part are replaced by automated actions conducted by agents on our behalf.
Implications for Consumers | Description |
Hyper-Personalization at Scale | Software evolves from offering generic interfaces to providing experiences tailored to individual behavior, preferences, and context. Streaming services, for example, use AI to not only recommend content but also to continuously optimize the entire user journey in real-time (Source 3.3). |
Shift to Agentic Interfaces | Users will rely less on visiting websites or navigating apps and more on asking AI agents or virtual assistants to perform tasks on their behalf (e.g., "book me the cheapest flight next month," "draft a marketing email"). This means brand interaction and loyalty may shift from the app's visual design to the seamlessness of the agent's performance (Source 3.2). |
Proactive Functionality | Apps will shift from being reactive to proactive. They will anticipate needs and offer solutions before the consumer realizes the problem. Examples include predictive analytics flagging potential issues (e.g., a subscription service detecting a user is at-risk of churning and offering a deal instantly) (Source 3.1). |
Privacy and Transparency Concerns | The increased depth of personalization requires collecting and analyzing vast amounts of personal data. This amplifies consumer concerns about how their information is being used and potentially compromised, making AI ethics and transparency a core component of building user trust (Source 3.7). |
Potential for "Experience Constraint" | Over-reliance on personalization risks creating "echo chambers," where the AI constrains the user's experience by only showing them content or options that align with past behavior, potentially limiting discovery or the formation of new preferences (Source 3.6). |
Business models might change as much as they did when replaced by cloud-based supply: “shrink-wrapped software” purchases replaced by subscriptions; placed-based access by “anywhere access;” operational expense substituted for capital expense.
Aspect of Transformation | Cloud Computing Model Shift | AI/Generative AI Model Shift | Source Link |
Fundamental Business Model | Capital Expenditure (CAPEX) to Operating Expenditure (OPEX). (Move from owning to renting IT infrastructure). | Product Sales to Insights/Agent-as-a-Service. (Move from selling software to selling autonomy and outcomes). | The Cloud Shift, The AI Shift |
Core Value Delivered | Agility, Elastic Scalability, and Cost Efficiency. (The ability to scale infrastructure instantly). | Hyper-Personalization, Prediction, and Automation. (The ability to perform tasks and anticipate needs). | Cloud Transformation, AI's Impact on Innovation |
Pricing Model | Subscription (SaaS) or Usage-Based (IaaS/PaaS) on a per-resource/per-seat basis. | Usage/Consumption-Based, Value of Insights, Dynamic Pricing, or Outcome-Based Billing (Source 2.3). | Cloud Cost Optimization, AI-Driven Profit Centers |
Impact on Consumer Experience | Accessible from Anywhere (Mobility) and increased application reliability (uptime). | Autonomous Agents providing 24/7, proactive, and Real-Time Functionality. | Cloud Benefits, AI in Customer Experience |
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