• Machine customer

It is a nonhuman entity-such as software, an AI agent, a virtual assistant, or even an IoT device-that makes decisions and purchases autonomously instead of a person.

Practical examples

• • Printer smart that automatically orders new cartridges when they are running low.

• • Electric vehicle that buys its own energy or books a charging point on a route-by-route basis.

• • Enterprise AI assistant who buys software licenses or cloud services based on actual consumption.

Gartner predicts that within a few years the machine customers will become millions, transforming markets because suppliers will no longer talk only to human customers, but also to “machine customers” who make decisions based on data and algorithms.

• Self-adaptive products

They are designed for:

• • monitor the environment, resource utilization, and its own performance through sensors or software,

• • process the data with AI/ML algorithms,

• • adapt in real time , changing functions, parameters or behavior to provide the best possible experience.

How they work:

• • Input → the product collects data (e.g., location, wear and tear, user preferences, environmental conditions).

• • Processing → an AI engine analyzes the data in real time.

• • Adaptation → the product changes its settings or suggests optimal actions.

• • Feedback loop → learns from behavior and progressively improves.

Concrete examples

• • Self-adaptive software : an ERP system that modifies reports and dashboards based on managers’ usage patterns.

• • Industrial smart machines : an assembly line that automatically adjusts speed and parameters to reduce defects or energy consumption.

• • Consumer products : headphones that automatically adjust noise reduction according to the environment; a thermostat that learns family habits and adjusts the temperature.

Concrete opportunities of Autonomous Business

• Automated supply chain: an AI agent can monitor stock levels, compare supplier prices, automatically order materials, and renegotiate contracts when market conditions change.

• Intelligent customer care: Advanced chatbots that don’t just respond, but anticipate the customer’s needs (e.g., they order parts before a machine breaks down).

• Autonomous predictive maintenance: Machines that report an impending failure, order spare parts, and schedule service without human intervention.

• Programmable marketplaces: B2B platforms where AI business agents negotiate prices, delivery times and production capacity with each other.

• Self-adaptive products: Industrial machinery that configure themselves according to the batch to be produced, reducing setup times and errors.

2.Hypermachinity

Position in the Hype Cycle: Peak of inflated expectations (second stage)

La Hypermachinity represents the philosophy and development of systems ultra-intelligent and autonomous , capable of going beyond traditional human-machine boundaries. It is not just about automation, but machines that are self-organizing, learning and creating solutions in a similar – and sometimes superior – way to humans.

Key Technologies

• AGI (Artificial General Intelligence) : artificial intelligences not limited to specific tasks, but capable of learning and adapting to different contexts.

• • For example, an AGI system could analyze clinical data, make preliminary diagnoses, and then apply the same reasoning model to optimize a company’s supply chain.

• • Or an AGI could handle space mission planning autonomously, learning from previous scenarios and adapting to unforeseen conditions.

• • In education, an AGI could act as a universal tutor, adapting the teaching method to each student, seamlessly moving from math to literature.

• Embodied AI : intelligence embodied in robots or physical devices that interact with the environment.

• • Smart household robots: capable of recognizing objects, moving them, cleaning or cooking by adapting to the family’s habits.

• • Collaborative industrial robots (cobots): learn by observing human operators and adjust force and movement to perform delicate or complex assemblies.

• • Autonomous vehicles: cars, drones, or robots for last-mile logistics that sense their surroundings, make decisions, and interact with real traffic, pedestrians, or obstacles.
    

• Humanoid robots : machines with human-like features and movements, useful in service, logistics, manufacturing:

• • Assisting the elderly or frail patients: robots that walk, talk, and help with daily activities, such as getting out of bed or remembering medications.

• • Front desk and customer service: humanoid robots employed in hotels, airports, or trade shows that greet visitors, provide information, and interact in multiple languages.

• • Support in production and logistics: robots that move into warehouses or assembly lines to transport materials, working side by side with operators.
    

• Meta computing : distributed networks that combine physical, digital, and cloud computing power to create adaptive “super-systems.”

• • Advanced industrial simulations: platforms that combine digital twins, IoT and distributed computing to optimize a plant’s production in real time.

• • Collaborative scientific research: supercomputer networks and clouds sharing resources for climate simulations or molecular modeling in pharmaceutics.

• • Large-scale immersive gaming: persistent virtual worlds with millions of users, managed by infrastructure that dynamically balances loads between physical and cloud servers.
    

In summary, the Hypermachinity is not just “more automation,” but the arrival of hyper-powerful autonomous systems that integrate AI, robotics, and high-performance computing (HPC), generating scenarios of great opportunity but also of high expectation (and consequent risk of disappointment).

Practical opportunities of Hypermachinity

• Advanced manufacturing : collaborative robots (cobots) that learn by observing operators and adapt their movements to perform complex assemblies without manual reprogramming.

• Healthcare : Assisting humanoid robots that support elderly patients at home, monitor vital signs and communicate with doctors.

• Logistics : autonomous drones that plan their own routes based on air traffic, weather, and delivery priorities.

• Scientific research : AGI systems that explore scientific hypotheses by simulating millions of scenarios in meta-computing, accelerating the discovery of new materials or drugs.

• Customer services. : embodied agents in stores or banks, able to recognize emotions, give personalized assistance, and learn from interactions.

3. Augmented Humanity – SLope of Enlightenment (fourth phase).

It is the set of technologies that amplify cognitive and physical abilities Of people (they do not replace them). Slope of Enlightenment Is the 4th phase of the Hype Cycle: after hype and disillusionment, Real-world use cases, best practices and measurable ROI emerge; tools mature and companies understand when e as adopt them.

Key Technologies

• Brain-Machine Interface (BMI/BCI)
  Non-invasive (EEG/EMG/eye-tracking): hands-free commands, fatigue detection, intent detection for contextual assistance.
  

• Adaptive UI / Adaptive interfaces.
  UIs that adapts to the role, context, and state of the user. : AR overlay that changes granularity, offline “just-in-time help,” workflow that shortens if the operator is experienced.
  

• Wearable AI & AR/MR.
  Smart glasses, wearable sensors, edge AI: component recognition, visual validations; lightweight exoskeletons for posture/effort.
  

• Human-machine collaboration (HRC)
  Cobots with shared control and geofencing; software co-pilots suggesting next actions; digital twin for as-built vs as-designed verifications.
  

• Basic enablers
  Sensing (camera/IMU/EEG), edge + cloud (5G/Wi-Fi 6, GPU), models CV/NLP , security and identity, telemetry.

Practical opportunities of Augmented Humanity

• Training immersive : AR/MR simulations of real procedures (machine setup, safety, rare failures) with immediate feedback and guided repetition. Onboarding of new operators becomes hands-on and tracked : each step is verified, errors are explained in context.

• Operators enhanced : “heads-up” step-by-step (hands-free) instructions, on-sight (AR check), on-device contextual help, and automatic evidence collection (photo/video/voice notes, code reading, parameters). Also works offline with deferred synchronization.

• Environments hybrid workplaces : a remote expert “sees what the operator sees,” notes in AR and guides resolution; meanwhile, the system automatically records who did what, when, and with what evidence (native audit trail linked to work order).

4.Techno-Societal Fragility – Trough of Disillusionment and Plateau of Productivity (between third and fifth stages)

It is the “dark side” of the technology cycle: when the initial enthusiasm fades, there emerge socio-technological frailties – critical dependencies, disinformation, vulnerable supply-chains, ransomware, distributed denial of service. The transition to the Plateau occurs when organizations incorporate resilience patterns and controls that make technology reliable on a day-to-day basis (security + business continuity).

Key Technologies

• Confidential Computing
  Execution on TEE (hardware enclave) that protects the data in use : encrypted even during processing. Reduces risk from compromised host and insider at the platform level.

A TEE (Trusted Execution Environment) is an isolated hardware area (“enclave”) where code runs with encrypted memory and limited access; it protects data and processes even if the operating system or hypervisor is compromised.

• Disinformation Security
  Content provenance. (e.g., C2PA, watermarking/attestations), bot detection/coordinated inauthentic behavior, pipeline of content authenticity end-to-end.

C2PA is an open standard for provenance/authenticity of content: it incorporates a signed manifest with hashes and metadata (acquisition, changes, device) into the files, so recipients can verify origin, change history, and tampering across multiple platforms.

• Crypto-Agility
  Architectures and policies for rotate keys/algorithms without rewriting systems (readiness for new ciphers, including post-quantum ), separation of crypto-policy and application code.

A cipher is a cryptographic algorithm that transforms plaintext into ciphertext using a key; the reverse operation (decryption) recovers the original with the correct key. It can be symmetric or asymmetric and operates through defined mathematical functions.

Practical opportunities of Techno-Societal Fragility

Strengthening resilience, security, technological sovereignty, the digital immune systems .

• Resilience: continuing to operate even with failures, with : multi-AZ/region, offline/outbox, rapid rollback, DR tested. KPIS: RTO/RPO, MTTR, % incidents with limited impact.

• Security: protect identity, data and supply chain, thanks to. : zero-trust (MFA/least-privilege), SBOM + attested builds, monitoring/IR. KPIS: MTTD/MTTR security, patch coverage, % assets with SBOM/attestation.

• Sovereignty technology: control over data/keys and portability (less lock-in), with : crypto-agility (rotatable keys/algorithms, PQ-ready), BYOK, open standards/containers/IaC. KPIS: Key rotation time, % portable workloads, cost/time of vendor switch.

• Digital Immune Systems: prevenire/detect/isolate/self-repair in production, through. : observability by design, canary/feature flags, shift-left testing, anti-fraud/content prevention. KPIS: error budget, post-release regressions, % canary rollout, % successful auto-remediation.

H ype Cycle 2025 – Map of Areas: Location, Description, Key Technologies and Practical Opportunities