Capabilities

AI and emerging technology security

Address the security exposures created by AI and emerging technologies as adoption expands across the enterprise.

Secure emerging technologies around the new exposures they create rather than extending yesterday's controls by default

We connect AI adoption, emerging attack surfaces and security requirements to clarify how new technologies can be deployed with controlled exposure.

AI and emerging technologies change both what organizations must protect and how attacks can occur. Models, training data, autonomous actions, new interfaces and rapidly evolving technology dependencies create exposures that may not fit established security controls. Adoption can also spread through the enterprise faster than governance can identify where systems are being used or what they can access. Security must therefore evolve alongside experimentation and scaling, distinguishing genuinely new risks from familiar ones expressed through new technologies and defining controls proportionate to the business consequences of failure or misuse.

AI security starts where new capabilities create unfamiliar attack surfaces

Models, agents and emerging technologies introduce risks across data, access, behavior and system interaction.

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Strategic Challenges

Can AI adoption move faster without leaving security behind?

The challenge is governing rapidly evolving technologies when controls, ownership and threat models are still immature.

Read now

Strategic Impacts

AI security makes emerging technology risk visible before deployment scales

Clearer controls around models, data and access help organizations distinguish experimentation from unmanaged exposure.

Read now

Observed Patterns

AI security programs often protect models while ignoring the systems around them

Weak identities, exposed data, unsafe integrations and poorly governed agents can matter more than the model itself.

Read now

Strategic Challenges

Can AI adoption move faster without leaving security behind?

The challenge is governing rapidly evolving technologies when controls, ownership and threat models are still immature.

Read now

Strategic Impacts

AI security makes emerging technology risk visible before deployment scales

Clearer controls around models, data and access help organizations distinguish experimentation from unmanaged exposure.

Read now

Observed Patterns

AI security programs often protect models while ignoring the systems around them

Weak identities, exposed data, unsafe integrations and poorly governed agents can matter more than the model itself.

Read now

POV

AI does not need a separate security universe; it needs tougher threat assumptions

Treating AI as exceptional can obscure familiar control failures amplified by autonomy, scale and unpredictable behavior.

Read now

Our approach

Assess emerging technology security from use case and exposure through architecture and control

Our approach begins by identifying how AI and emerging technologies are being used, what they can access and which business outcomes could be affected by compromise, misuse or unintended behavior. We map technology-specific attack surfaces alongside established cyber risks to distinguish genuinely new exposures from familiar control requirements. Security requirements are then defined around data, models, identities, interfaces, infrastructure and third-party dependencies according to use-case criticality. We establish governance and monitoring priorities that can evolve as adoption expands and technology behavior becomes better understood.

The data and estimates presented are indicative and intended for illustrative purposes. Actual outcomes may vary based on each company’s specific context, market conditions, operating model, implementation choices, and the quality and consistency of execution, including actions undertaken by the client.

Keypillars

Explore the key pillars that define this capability and shape how we create focused, measurable business impact.

Threat visibility

Identifies security exposures introduced by AI systems, emerging technologies, new interfaces, model dependencies, and evolving attack surfaces

Control adaptation

Aligns security controls with the distinct risks of AI, autonomous systems, advanced computing, and rapidly changing technology environments

Technology assurance

Establishes governance, testing, and oversight practices for assessing whether emerging technologies operate within defined security boundaries

Are you securing emerging technologies before adoption expands the attack surface beyond your control?

Get in touch with our AI and emerging technology security team to examine exposure, controls and technology-specific security requirements.

Get in touch

Strategic Framework

Explore our Strategic Framework

Explore our strategic framework applied to page_title and discover which model we apply to help you achieve your goals and objectives.

Discover our framework

01. Map exposure

Identify security risks across AI systems, models, data flows, agents, interfaces, and emerging technology dependencies

06. Monitor evolution

Track emerging threats, technology changes, control effectiveness, and new exposure across the technology landscape

05. Test resilience

Examine how systems respond to adversarial behavior, failure modes, misuse scenarios, and control breakdowns

02. Assess controls

Evaluate existing safeguards against model misuse, data leakage, manipulation, unauthorized access, and technology abuse

03. Set guardrails

Define security requirements, control boundaries, usage conditions, and escalation rules for emerging technologies

04. Design protections

Embed security across architecture, data, access, model lifecycle, interfaces, monitoring, and operational workflows

How we help

Identify and control the security exposures created as AI and emerging technologies move from experimentation to scale

We provide security strategies for AI and emerging technologies across use cases, models, data, infrastructure and technology dependencies. The work can include AI security assessments, attack-surface analysis, control requirements, secure adoption principles, third-party exposure and emerging-risk monitoring. Outputs clarify which new technologies create material security implications, how existing cyber controls should adapt, where novel safeguards are required and what governance should accompany adoption as systems become more autonomous, connected or consequential to business operations.

AI security risk assessment
AI threat modeling
AI security architecture
Model access security
AI data protection
Prompt injection risk assessment
Model extraction protection
AI supply chain security
AI application security
Agentic AI security
AI identity and authorization
AI misuse prevention
AI monitoring and detection
AI incident response
Emerging technology risk assessment
Autonomous system security
Quantum security readiness

Article

Digital transformation after the transformation era

Why the next digital agenda is less about isolated programs and more about architecture, platforms, governance and measurable enterprise value.

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Case study

Intelligent revenue engine for an international hospitality group

Connecting demand, pricing, CRM and AI to personalize the customer experience and optimize occupancy, conversion and lifetime value.

View case study

Explore our FAQs

Find answers to the most common questions about this service, including key features, processes, and practical considerations. Explore our FAQs for additional insights and guidance.

AI introduces model, data, prompt, dependency and misuse risks that require controls beyond conventional application and infrastructure security.

Prioritize exposure involving sensitive data, model misuse, access control, third-party dependencies and decisions with material business impact.

Controls should reflect data sensitivity, model autonomy, external connectivity, decision impact and the consequences of incorrect outputs.

They provide a foundation, but AI-specific risks such as model manipulation, prompt abuse and training-data exposure need additional controls.

Assess provenance, access, data handling, update mechanisms, dependencies and the controls surrounding deployment and ongoing use.

Monitor access, anomalous use, data exposure, model behavior, dependency changes and incidents that could alter the system's risk profile.

Use explicit risk ownership, bounded experimentation, proportionate controls and periodic reassessment as technologies and threat patterns evolve.

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Editorial overview

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Digital trust becomes a growth constraint

Why cybersecurity, identity and information integrity increasingly shape whether companies can scale digital channels, AI and connected ecosystems.

Read article

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How modular platforms, APIs and modernized applications can reduce structural complexity while accelerating digital products and AI adoption.

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Focus

Get in touch

Get in touch with our experts to discuss your priorities, explore potential opportunities, and understand how our capabilities can support your organization.

AI and emerging technology security

Address the security exposures created by AI and emerging technologies as adoption expands across the enterprise.

Secure emerging technologies around the new exposures they create rather than extending yesterday's controls by default

We connect AI adoption, emerging attack surfaces and security requirements to clarify how new technologies can be deployed with controlled exposure.

AI security starts where new capabilities create unfamiliar attack surfaces

Models, agents and emerging technologies introduce risks across data, access, behavior and system interaction.

Can AI adoption move faster without leaving security behind?

The challenge is governing rapidly evolving technologies when controls, ownership and threat models are still immature.

AI security makes emerging technology risk visible before deployment scales

Clearer controls around models, data and access help organizations distinguish experimentation from unmanaged exposure.

AI security programs often protect models while ignoring the systems around them

Weak identities, exposed data, unsafe integrations and poorly governed agents can matter more than the model itself.

Can AI adoption move faster without leaving security behind?

The challenge is governing rapidly evolving technologies when controls, ownership and threat models are still immature.

AI security makes emerging technology risk visible before deployment scales

Clearer controls around models, data and access help organizations distinguish experimentation from unmanaged exposure.

AI security programs often protect models while ignoring the systems around them

Weak identities, exposed data, unsafe integrations and poorly governed agents can matter more than the model itself.

AI does not need a separate security universe; it needs tougher threat assumptions

Treating AI as exceptional can obscure familiar control failures amplified by autonomy, scale and unpredictable behavior.

Assess emerging technology security from use case and exposure through architecture and control

Are you securing emerging technologies before adoption expands the attack surface beyond your control?

Get in touch with our AI and emerging technology security team to examine exposure, controls and technology-specific security requirements.

Explore our Strategic Framework

Explore our strategic framework applied to page_title and discover which model we apply to help you achieve your goals and objectives.

01. Map exposure

06. Monitor evolution

05. Test resilience

02. Assess controls

03. Set guardrails

04. Design protections

Identify and control the security exposures created as AI and emerging technologies move from experimentation to scale

What makes AI systems different from traditional technology security risks?

Which AI risks should organizations assess first?

How should security controls differ across AI use cases?

Can existing cybersecurity frameworks cover AI security adequately?

How should organizations secure externally sourced AI models?

What should be monitored after an AI system is deployed?

How should emerging technology risk be governed before standards mature?

Get in touch

Get in touch with our experts to discuss your priorities, explore potential opportunities, and understand how our capabilities can support your organization.