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Executive Summary

This report examines the impact of artificial intelligence (AI) on software engineering processes and developer hiring trends across six major companies: Duolingo, Inc., ASGN Incorporated, Cadence Design Systems, Inc., Grid Dynamics Holdings, Inc., The Hackett Group, Inc., and Cognizant Technology Solutions Corp. The analysis finds that while AI tools are substantially improving efficiency in coding, content creation, and design automation, they have not universally led to a slowdown in hiring for software engineering roles. Instead, companies are increasing investments in AI, focusing on upskilling existing talent and actively recruiting AI-competent developers. Traditional developer roles may see moderate changes, with specialized AI-related positions gaining prominence. Macroeconomic conditions exert a broader influence on hiring than the direct effects of AI coding tools. Overall, AI is viewed less as a replacement for developers and more as a capability enhancer and catalyst for organizational transformation.

Introduction

The objective of this report is to provide a comparative analysis of how AI adoption influences software engineering workflows and the corresponding hiring strategies for software developers. Focusing on six publicly traded companies from diverse sectors, the report synthesizes their latest disclosures to assess trends in demand for engineering talent, the evolution of development processes in light of AI-driven tools, and the approaches taken to retrain or upskill their workforce. The methodology follows a qualitative comparison of company statements and operational data, identifying sector-wide patterns and company-specific strategies.

Impact of AI on Software Engineering Processes AI-Driven Content Creation and Automation

AI coding tools have enabled significant gains in task automation and large-scale content generation. Duolingo, for example, leverages AI to produce language courses and subject content at a rate previously unimaginable—achieving in one year what once took over a decade. Cadence Design Systems and The Hackett Group report similar advances, with AI tools expediting content, ideation, documentation, and code conversion tasks. Across these companies, AI-driven automation translates to accelerated time-to-market, enhanced scalability, and productivity improvements that were previously unattainable.

AI in Design and Verification

In specialized domains such as semiconductor design, Cadence has integrated AI across over half its workflows. Their solutions, like Cerebrus and SimAI, deliver exponential improvements in design verification, slashing turnaround times and optimizing outcomes (up to 20x faster performance and 83% reduction in certain metrics). These enhancements are fueling investments in next-generation technologies and broadening the applicability of AI to adjacent engineering functions like PCB design and complex system packaging.

Operational and Platform Engineering Enhancements

Companies like Grid Dynamics and The Hackett Group illustrate the growing sophistication of AI in platform development, multi-modal engineering, and operational scaling. AI not only supports the deployment of advanced agentic platforms but also underpins new approaches to client engagement and value delivery. These companies are adopting enterprise-scale AI solutions that enable measurable business outcomes and drive demand for engineers skilled in platform automation, search solutions, and end-to-end AI orchestration.

Hiring Trends in the Presence of AI Coding Tools Demand for AI-Competent Developers

The persistent theme across all companies is a strong—often increasing—demand for developers with AI, GenAI, automation, and data engineering expertise. ASGN and The Hackett Group highlight continued expansion in hiring, including aggressive recruitment in offshore locations and strategic acquisitions to build AI-centered talent pools. Grid Dynamics emphasizes the value of senior and mid-level engineers in AI disciplines and maintains a consistent hiring strategy, underpinned by internal upskilling and deep client partnerships.

Impact on Traditional Software Engineer Roles

While AI tools are automating portions of routine coding and content development, most companies report no major slowdown in hiring for traditional software engineering roles. Duolingo and Cadence, for instance, stress the ongoing necessity of human engineers to maintain and evolve complex existing codebases and manage advanced AI toolchains. Cognizant notes some optimization and potential slowdown in hiring for routine development positions, where AI-led automation supports cost takeout. However, this tends to be offset by a rising need for engineers capable of leveraging or building AI systems.

Upskilling and Talent Development Initiatives

In response to shifting technology demands, companies are prioritizing robust upskilling and training initiatives. Cognizant has established learning centers to train large swathes of its workforce in AI competencies. Grid Dynamics and The Hackett Group augment internal pipelines through internships and structured upskilling programs. This focus ensures a future-ready workforce adept at using AI tools rather than being supplanted by them.

Comparative Company Analyses Duolingo, Inc. (DUOL)

AI has empowered Duolingo to dramatically increase its content generation capacity and efficiency. The company continues to hire engineers for developing AI-driven features, citing ongoing demand as AI is not yet capable of autonomously maintaining complex codebases. There is no evidence of a slowdown in developer hiring as a result of AI deployment; rather, AI is seen as an augmentation tool.

ASGN Incorporated (ASGN)

ASGN reports sustained client investment in AI, agent assistance, and automation, translating to ongoing demand for technical talent in AI, data, and cloud roles. There is no direct link between AI coding tools and hiring slowdown; rather, overall macroeconomic caution shapes IT spending. The company retains resilience through a flexible labor model and acquisition strategy.

Cadence Design Systems, Inc. (CDNS)

AI is integral to Cadence’s semiconductor design workflows, yielding significant boosts in productivity. The trend is not toward staff reduction; skilled engineers remain central to managing and advancing AI-enabled toolchains. Hiring continues robustly in line with technological advancements and business needs.

Grid Dynamics Holdings, Inc. (GDYN)

Grid Dynamics’ delivery of AI-based solutions supports both operational excellence and strong client engagement. The company maintains a record billable employee base, with hiring focused on AI and platform engineering. Strategic upskilling and international expansion (notably in India) underpin its talent strategy, countering any potential impact from AI coding automation.

The Hackett Group, Inc. (HCKT)

The Hackett Group’s AI Explorer platform and associated technologies drive new business opportunities and the need for expanded technical teams. The company invests significantly in hiring and scaling talent, particularly through offshore expansion and acquisitions. There is no sign of hiring slowdown due to AI tools; growth is instead oriented around AI solutions development.

Cognizant Technology Solutions Corp. (CTSH)

Cognizant is experiencing a shift as AI-written code now exceeds 20%. While automation may be leading to a moderate slowdown in traditional developer hiring, the demand for AI-competent engineers, freshers, and upskilling initiatives is robust. The company is proactively reskilling its workforce to align with evolving technological needs.

Cross-Company Comparative Analysis Efficiency Gains vs. Headcount Strategies

All six companies report substantial efficiency improvements through AI-driven automation and workflow enhancements. However, rather than universally reducing headcounts, these gains are prompting shifts in the type of engineering talent sought—more specialized, AI-competent, and higher-value roles are prioritized over routine developers.

Evidence of Hiring Slowdown

Except for some signs at Cognizant (where automation may be slowing traditional developer recruitment), there is scant evidence of a broad-based slowdown in developer hiring driven purely by AI tools. Macroeconomic uncertainties have a greater effect on hiring rates than automation-induced efficiencies at this stage.

Talent Development and Retention Approaches

Across the board, companies are investing in upskilling, AI training programs, and talent development pipelines—particularly emphasizing internships, internal rotations, and strategic recruitment in locations with abundant technical talent (e.g., India). Retention is further supported by engaging employees in challenging AI-centric projects.

Industry Outlook and Future Implications

Looking ahead, AI is set to continue reshaping software engineering by further automating routine tasks and generating new classes of work around AI platform integration, monitoring, and governance. Demand for traditional software developers may taper as process automation deepens; however, the requirement for AI-literate engineers, solution architects, and data scientists will likely surge. Companies that couple efficiency gains with forward-thinking talent development strategies will be best positioned to capitalize on AI’s transformative potential while mitigating workforce disruption.

Conclusion

The integration of AI into software engineering processes is driving unprecedented productivity growth without triggering an immediate or universal contraction in developer hiring. Instead, companies are recalibrating talent strategies, accelerating the recruitment and development of AI-competent engineers, and investing in large-scale upskilling initiatives. Organizations are advised to proactively anticipate these shifts by fostering continuous learning cultures, diversifying talent pipelines, and exploring new workforce models aligned to the evolving demands of AI-enabled software development.

Future Outlook

2024 (Q4)

• The company is experiencing record growth, with Q4 revenue of $22.1 billion (up 265% YoY) and full-year revenue of $60.9 billion (up 126% YoY).
• Data center revenue is the primary driver, reaching $18.4 billion in Q4 (up 409% YoY), fueled by the Hopper GPU platform and InfiniBand networking.
• Demand for generative AI and large language models is surging across industries, with approximately 40% of data center revenue attributed to AI inference.
• Gross margins are at a peak (GAAP: 76%, non-GAAP: 76.7%), benefiting from favorable component costs, but are expected to normalize to the mid-70% range for the remainder of the year.
• The company is supply-constrained for next-generation products (Blackwell), with demand expected to outpace supply through 2024 and into 2025.
• The installed base of RTX PCs exceeds 100 million, with over 500 AI-enabled applications and games, and the company is ramping up new RTX 40 Series GPUs and AI laptops.
• Automotive and healthcare verticals are growing, with automotive data center revenue exceeding $1 billion and new DRIVE platform adoptions.
• The company is expanding its software and services business, reaching a $1 billion annualized run rate, and is investing in sovereign AI infrastructure globally.

2025 (Q4)

• Revenue continues to set records, with Q4 revenue of $39.3 billion (up 78% YoY) and full-year revenue of $130.5 billion (up 114% YoY).
• Data center revenue for the year is $115.2 billion, more than doubling from the prior year, with Q4 data center revenue at $35.6 billion (up 93% YoY).
• The Blackwell architecture is now in full production, with $11 billion in Q4 Blackwell revenue and the fastest product ramp in company history.
• Gross margins are temporarily lower (GAAP: 70.6%, non-GAAP: 71%) during the Blackwell ramp, expected to return to the mid-70% range as manufacturing efficiencies improve later in the year.
• Operating expenses are rising (GAAP: $5.2 billion, non-GAAP: $3.6 billion for Q1 2026), reflecting higher R&D and infrastructure costs for new product introductions.
• The company expects continued strong demand, with Q1 2026 revenue guidance at $43 billion and sequential growth in both data center and gaming.
• The product roadmap is accelerating, with Blackwell Ultra launching in the second half of 2025, followed by Vera Rubin and other next-generation platforms.
• The company is at the forefront of new AI scaling laws, with post-training and inference (reasoning AI) requiring orders of magnitude more compute than pretraining.
• The installed base is being leveraged for both legacy and new workloads, with CUDA compatibility across generations.
• The company is expanding into physical AI and robotics, with the Cosmos World foundation model platform and growing adoption in automotive and industrial sectors.
• Geographically, the US is driving the majority of growth, with China remaining at a reduced but stable percentage due to export controls.

Performance

2024

• Exceptional revenue and profit growth, driven by surging demand for AI infrastructure.
• Gross margins at historical highs, aided by favorable supply chain dynamics.
• Supply constraints for new products (Blackwell) are a limiting factor, but overall supply is improving.
• Strong growth in gaming, professional visualization, automotive, and healthcare verticals.
• Software and services are becoming a more significant revenue stream.

2025

• Revenue and data center growth accelerate further, with Blackwell architecture driving a new wave of adoption.
• Gross margins dip during the Blackwell ramp but are expected to recover as production scales and costs improve.
• Operating expenses increase due to heavy investment in R&D and infrastructure.
• The company maintains a strong balance between supporting legacy products and ramping new architectures.
• The product cadence is annual, with clear visibility for customers and partners, supporting smooth transitions and sustained demand.

Product Lineup

2024

• Hopper GPU platform is the flagship, with H100 and H200 products leading in AI training and inference.
• RTX 40 Series GPUs and AI laptops are expanding the gaming and creator ecosystem.
• DRIVE Orin and DRIVE Thor are advancing automotive AI, with new customer wins and platform adoptions.
• Spectrum-X networking is introduced, targeting AI-optimized data center networking.
• Software stack (CUDA, AI Enterprise) and cloud services (DGX Cloud) are gaining traction.

2025

• Blackwell architecture becomes the new flagship, with rapid adoption and multiple configurations (air/liquid cooled, customizable systems).
• Blackwell Ultra launches in H2 2025, maintaining the company’s annual product cadence.
• Vera Rubin and other next-generation platforms are in development, with partners already preparing for transitions.
• The product stack is increasingly unified, supporting pretraining, post-training, and inference on a single platform.
• Expansion into physical AI and robotics, with the Cosmos World platform and growing automotive/robotics partnerships.
• Networking advances with NVLink 72 and Spectrum X, supporting larger and more complex AI clusters.

Key Changes and Implications

• Transition from Hopper to Blackwell: The most significant change is the shift from Hopper to Blackwell as the core architecture, with Blackwell delivering substantial performance and efficiency gains, especially for reasoning AI and inference workloads.
• Scaling Laws and Compute Demand: The emergence of new AI scaling laws (post-training, inference scaling) is driving exponential growth in compute demand, positioning the company’s unified architecture as essential for future data centers.
• Product Cadence and Roadmap Clarity: The company’s annual product cadence (Blackwell, Blackwell Ultra, Vera Rubin) provides customers and partners with clear visibility, supporting smooth transitions and sustained demand.
• Gross Margin Dynamics: Margins are temporarily lower during the Blackwell ramp due to higher manufacturing and component costs but are expected to recover as production scales.
• Geographic and Vertical Expansion: The US leads growth, but sovereign AI and verticals like automotive, healthcare, and robotics are becoming increasingly important. China remains constrained by export controls.
• Software and Services Growth: The software and services business is scaling rapidly, with AI Enterprise and cloud offerings becoming more material to overall results.
• Physical AI and Robotics: The company is moving beyond digital AI into physical AI and robotics, opening new markets and applications.

Summary Table Conclusion

The period from Q4 2024 to Q4 2025 marks a pivotal transition for the company, with the Blackwell architecture driving a new era of AI infrastructure, expanding into reasoning AI, physical AI, and robotics. Revenue and data center growth accelerate, gross margins temporarily compress during the product ramp, and the product roadmap becomes more ambitious and transparent. The company’s unified architecture, annual product cadence, and expanding software/services business position it for continued leadership in the rapidly evolving AI and accelerated computing landscape.

Executive Summary

This report analyzes the merchandising strategies adopted by leading industry players in response to tariffs, with a focus on supply chain, sourcing, pricing, and operational adaptations. Drawing from the most recent company disclosures and earnings transcripts of Visteon Corporation, Novanta Inc., Masimo Corporation, Terex Corporation, Air Lease Corporation, and The ODP Corporation, it identifies common trends and company-specific approaches aimed at mitigating tariff impacts while sustaining growth and competitiveness. Key strategies include supply chain regionalization, diversification, cost containment initiatives, the use of value-based merchandising, and enhanced operational flexibility. The report concludes with cross-industry insights and actionable recommendations for both immediate and long-term resilience in a tariff-impacted environment.

Introduction

Tariffs have become a pivotal factor in shaping global industry strategies, directly affecting both supply chains and merchandising approaches. As tariff policies shift in response to geopolitical dynamics and trade negotiations, companies across various sectors must navigate increased costs, supply chain disruptions, and evolving market demands. The objective of this report is to examine how major industry players are adjusting their merchandising strategies to address tariff challenges, outlining both tactical responses and long-term strategic positioning. The analysis offers a comprehensive view of the adaptive measures taken, setting a foundation for best practice sharing and future planning.

Tariff Landscape and Industry Impact

Recent years have seen the imposition of tariffs—especially between major economies such as the US and China—covering a broad range of goods, including manufactured components, finished products, and raw materials. The scope of these tariffs has compelled companies to reassess supply chain architectures, cost structures, and product sourcing decisions. The direct impacts include increased landed costs, supply instability, inventory valuation changes, and more complex contract negotiations with both suppliers and customers. The uncertainty and periodic escalation or easing of tariffs further intensify the need for agile and diversified merchandising approaches to sustain competitiveness and margins.

Key Merchandising Strategies Supply Chain Reconfiguration

To minimize tariff exposure, companies are increasingly shifting production to regions not subject to certain tariffs, notably USMCA-compliant countries such as Mexico. Supplier diversification is also prevalent, with secondary sourcing in alternative countries (e.g., Vietnam, Indonesia, Malaysia) and increased local sourcing. In-market manufacturing for local demand (e.g., manufacturing in China for the Chinese market) and customized regional supply chains are being implemented to create “tariff-proof” operations.

Production Footprint Optimization

Enterprises are relocating manufacturing facilities or creating dual manufacturing lines across geographies as a direct response to tariff risks. For instance, setting up duplicate production capacity in Europe or North America aligns supply with demand in a way that bypasses certain tariffs. Forward inventory placement—strategically pre-positioning stock ahead of announced tariffs—also helps smooth cost impacts and supply disruptions.

Sourcing and Inventory Management

Mitigation strategies include shifting the product mix towards categories less impacted by tariffs and enhancing inventory management practices. Timing shipments, adjusting inventory levels, and even selectively quitting orders that are no longer cost-effective are common to manage the financial impact of tariff-induced price increases.

Pricing and Contractual Approaches

Companies deploy surcharges, implement price increases, or negotiate cost pass-through mechanisms with customers to recover tariff-induced costs. Long-term agreements with escalation caps are being used to contain risks in sectors like aerospace. Where possible, companies pass through these costs to end customers, maintaining price/cost neutrality.

Product and Market Diversification

To buffer against tariff volatility, firms are expanding into less-affected markets (such as domestic or USMCA regions), launching differentiated and value-added products, and shifting towards value-based rather than high-low merchandising. Market focus is also directed toward resilient sectors like healthcare, infrastructure, and areas with stable demand profiles.

Operational Flexibility and Technological Solutions

Investments in digitization, automation, and flexible operational structures allow companies to rapidly adjust to market and trade policy shifts. Organizational changes, such as shifting from product to regional sales teams, and the use of advanced management systems enhance agility and responsiveness.

Strategic Planning and Scenario Analysis

Given the ongoing uncertainties surrounding tariffs, robust scenario analysis and detailed mitigation planning are vital. Companies develop contingency plans for supply chain reconfiguration or pricing based on potential policy changes, ensuring readiness to act once clarity emerges.

Comparative Company Case Studies

The table below presents a comparative overview of merchandising strategies by company:

Visteon Corporation

Visteon has responded to tariffs by shifting production to Mexico, leveraging USMCA-compliant facilities, and diversifying its supplier base to reduce exposure to tariff-affected imports. The company has actively negotiated cost recovery with OEM customers, working to pass through tariff costs. Supply chain simplification and optimization, along with expanding domestic and less-affected foreign markets, are central to its strategy. Visteon's approach incorporates ongoing scenario planning and a strong focus on operational flexibility.

Novanta Inc.

Novanta’s response centers on sourcing adjustments—pivoting to tariff-exempt vendors and expanding manufacturing in regions like China and Europe to serve respective local markets. The company has adopted long-term regionalization strategies and duplicate manufacturing lines. Pricing adjustments, such as surcharges and increases, are applied to maintain margin. Cost containment initiatives and strategic acquisitions for market diversification bolster the approach. Robust scenario analysis and a commitment to permanent tariff mitigation underpin these measures.

Masimo Corporation

Masimo is aggressively altering its supply chain, moving certain production out of China and Malaysia, and exploring more domestic sourcing. Inventory management practices are carefully tuned, leveraging shipment timing and product mix to smooth out tariff costs. The company adopts both short and long-term pricing strategies while engaging in detailed scenario planning to adapt as tariff negotiations evolve. Organizational restructuring is considered to enhance responsiveness.

Terex Corporation

Terex focuses on balancing its supply chain by forward-placing inventory, rebalancing sourcing, and collaborating with global suppliers. Pricing strategies include the use of surcharges and localized price adjustments to maintain neutrality. Investments in digital tools and automation boost operational flexibility, while the company targets resilient end-markets and US-based or USMCA-compliant manufacturing sites. Tariff developments are closely watched, with plans adapted accordingly.

Air Lease Corporation

Air Lease minimizes direct tariff impact through contractual agreements that place responsibility for tariffs on airline customers, not the lessor. The company leverages long-term purchase agreements with escalation caps and maintains flexible fleets and delivery schedules. Adaptability is reinforced through a strong balance sheet, conservative capital management, and readiness for both organic and inorganic growth as market conditions allow.

The ODP Corporation

ODP’s response involves shifting away from high-low pricing to value-based merchandising, focusing on categories and products less affected by tariffs. Sourcing is diversified, with a reduction in imports from tariff-heavy locations and an increase in domestic procurement. The company manages inventory rigorously, adjusts pricing with suppliers, and maintains operational agility through disciplined management systems.

Cross-Industry Insights

Common strategies across companies include:

• Regionalization and Diversification: Nearly all profiled companies are moving toward more regionally based supply and production networks.
• Cost Pass-Through: Price adjustments, surcharges, and renegotiations of contract terms are widely implemented.
• Product/Market Shifts: Emphasis on value-oriented merchandising and a pivot to more resilient or less tariff-exposed markets is evident.
• Operational Flexibility: Investments in technology, management systems, and structural adjustments are enabling rapid responses to tariff changes.
• Scenario Analysis: Proactive, detailed planning for various tariff scenarios is universal, though the specifics differ by sector.

Differences arise in the nature of contractual risk management (notably in leasing versus manufacturing), the degree of international supply chain complexity, and the emphasis on innovation versus cost containment.

Recommendations Short-Term Actions

• Rebalance Sourcing: Immediately identify and shift critical sourcing to low-tariff or exempt regions where feasible.
• Review and Adjust Pricing: Implement surcharges or re-negotiate contracts with customers and suppliers to ensure cost recovery.
• Enhance Inventory Management: Adjust inventory holding and shipment timing to manage cost impacts around tariff threshold dates.
• Strengthen Day-to-Day Agility: Empower management teams with tools and processes for quick decision-making in response to evolving tariff news.

Long-Term Strategies

• Invest in Regional Production: Establish or expand regional manufacturing and duplicate production lines to insulate operations from tariff risks.
• Diversify Product and Market Portfolio: Develop or acquire products and expand into markets with lower tariff volatility or higher resilience.
• Digitize and Automate Operations: Invest in advanced technology for supply chain, inventory, and management systems to enhance responsiveness.
• Deepen Scenario Planning: Regularly update and rehearse detailed mitigation plans for a range of tariff and trade negotiation outcomes.

Conclusion

In the current tariff environment, effective merchandising strategies hinge on agile supply chains, proactive pricing, regional diversification, and robust scenario planning. The examined companies demonstrate various adaptive measures that balance short-term mitigation with long-term resilience-building. As tariff landscapes continue to evolve, continual investment in operational flexibility and strategic foresight will be essential for maintaining competitiveness and sustaining growth.

CrowdStrike Holdings, Inc. is leveraging AI extensively across its products and operations, positioning itself as a cybersecurity leader in the AI era. The company’s approach can be summarized in the following key areas:

1. AI-Native Security Operations Center (SOC) and Products

• Falcon Platform as AI-Native SOC: CrowdStrike’s Falcon platform is described as an AI-native SOC, integrating AI deeply into security operations to stop breaches effectively.
• Charlotte AI Security Analyst: A generative AI tool named Charlotte acts as a security analyst assistant, accelerating SOC operations and threat response times. It automates tasks such as activity summarization on hosts and users, reducing manual effort from 20-30 minutes to 10-15 seconds, as reported by customers.
• Agentic AI Models: CrowdStrike leverages its rich, contextualized threat data (curated with millions of Falcon Complete analyst annotations) to create agentic AI models that continuously improve protection and detection capabilities.

2. AI-Driven Threat Intelligence and Market Leadership

• CrowdStrike is recognized as the market’s leading threat intelligence authority, using AI to discover and name adversaries, especially in a landscape where AI-powered cyber threats are proliferating rapidly.
• The company’s threat intelligence practice saw record activity in Q4, highlighting its role in countering nation-state cyber operations and adversarial AI adoption.

3. AI Integration Across Business Functions

• CrowdStrike mandates every team and function within the company to leverage AI, expecting these investments to drive both top-line growth and bottom-line efficiencies on the path to $10 billion in Annual Recurring Revenue (ARR).
• Internally, AI tools have saved employees significant time, with reported average time savings of over one full workday per employee per month, equating to more than 24,000 work weeks saved annually across the workforce.
• AI is also used to automate key sales processes, streamline reporting, and improve workflow efficiency, enabling the company to focus on growth initiatives.

4. AI-Enabled Product Innovation and Market Expansion

• CrowdStrike’s AI capabilities underpin its cloud security, identity protection, and next-gen SIEM businesses, which collectively represent over $1.3 billion in ending ARR and are growing nearly 50% year over year.
• The next-gen SIEM product, combined with native first-party data and Charlotte AI, provides unmatched speed, scalability, and cost efficiency, positioning CrowdStrike as a leader in the AI security revolution.
• Exposure management, which includes vulnerability and attack surface management, leverages AI and integrated data to improve vulnerability prioritization and attack path analysis, enabling customers to replace legacy products at scale.

5. Falcon Flex Subscription Model and AI Adoption

• The Falcon Flex subscription model facilitates flexible adoption of AI-powered modules, accelerating platform adoption and customer consolidation on the Falcon platform.
• Customers adopting Falcon Flex are increasingly deploying multiple modules, with an average of more than nine modules per customer, reflecting deep integration of AI-driven security capabilities.
• The model supports attaching AI innovations like Charlotte AI to customer workflows, enhancing operational efficiency and security outcomes.

6. Strategic Positioning in the AI Era

• CrowdStrike emphasizes its role in “manufacturing the instruments to win the AI war,” highlighting its innovation engine fueled by proprietary security data.
• The company views AI as critical to securing cloud workloads, data centers, and edge devices, all of which are core areas of its market leadership.
• CrowdStrike is actively addressing the challenges of securing AI environments, including identity and data protection, in a rapidly evolving geopolitical and technological landscape.

Summary: CrowdStrike is deeply embedding AI into its cybersecurity platform, products, and internal operations. Its AI-native Falcon platform, powered by advanced threat intelligence and generative AI tools like Charlotte, enhances detection, response, and operational efficiency. The company’s AI investments are driving significant customer adoption, product innovation, and market leadership, positioning CrowdStrike as a pivotal player in securing the AI-driven future.

Strategic Implications and Expected Benefits of the Partnership with OpenAI for IAC InterActive Corp.

1. Innovation Leadership and Competitive Advantage

   • The partnership with OpenAI positions IAC at the forefront of AI innovation, giving the company a "seat at the table" with a leading AI pioneer. This strategic alignment allows IAC to influence and integrate cutting-edge AI technologies into its products and services early, enhancing its competitive edge.
   • Neil Vogel emphasized that OpenAI has been a "really good partner," with cooperative engineering efforts that have helped both parties roll out new products. This collaboration is unique compared to other AI providers, indicating a strong, productive relationship that benefits IAC’s innovation pipeline.

2. Enhanced Product Development and AI Integration

   • The partnership has directly contributed to advancements in IAC’s ad targeting capabilities, particularly through D/Cipher and D/Cipher Plus, which leverage AI for improved modeling and targeting. OpenAI’s assistance has been "a very big help" in decipher targeting and AI-driven modeling, enhancing the precision and effectiveness of IAC’s advertising technology.
   • AI is being applied across multiple IAC portfolio companies, including Vivian (healthcare staffing), Care (consumer care services), Turo (car sharing), and the Search business. These applications range from real-time bidding in advertising to smart matching and fraud detection, demonstrating broad utility and scalability of AI solutions enabled by the partnership.

3. Operational Efficiencies and Customer Experience Improvements

   • AI-driven automation is expected to transform customer service functions, with voice-driven AI handling level 1 and level 2 customer service representative (CSR) activities. This shift aims to create a better, more efficient customer experience, akin to the ATM revolution in banking, reducing reliance on traditional human interactions and improving service speed and quality.
   • Onboarding processes and marketing efforts are also benefiting from AI, with expectations of faster, more optimized marketing creative generation, testing, and placement through agentic AI, leading to improved marketing effectiveness over time.

4. Portfolio-Wide AI Opportunities and Growth Potential

   • Christopher Halpin highlighted that Vivian is the most aggressive and creative in applying AI, with other businesses like Care and Turo also exploring AI-driven opportunities. The presence of massive datasets in these businesses allows for optimization activities that provide real advantages, such as smart matching and fraud detection.
   • The AI integration is not limited to advertising but extends to operational and product enhancements, indicating a strategic move to embed AI deeply across IAC’s diverse portfolio, potentially driving growth and efficiency in multiple verticals.

5. Long-Term Strategic Vision and Market Positioning

   • The partnership supports IAC’s long-term strategy to innovate continuously and bring new ideas to market, as evidenced by recent launches like the People app, MyRecipes, and D/Cipher Plus. These initiatives signal to the market and advertisers that IAC is a dynamic, forward-looking company committed to leveraging AI for growth.
   • Neil Vogel and Christopher Halpin expressed confidence that the AI partnership will help IAC maintain leadership in digital publishing and advertising, enabling the company to adapt proactively to evolving market conditions and technological shifts.

Summary:
The partnership with OpenAI is a cornerstone of IAC’s strategy to drive future growth and innovation. It enables the company to integrate advanced AI capabilities into its advertising technology, product offerings, and operational processes, enhancing targeting precision, customer experience, and efficiency. This collaboration strengthens IAC’s competitive positioning across its portfolio, fosters continuous innovation, and supports long-term value creation by leveraging AI at scale.

Strategic Partnerships and Collaborations Update for Upcoming Fiscal Year

1. Partnerships with Leading AI Model Providers

   • Snowflake continues to actively collaborate with major AI foundation model providers rather than focusing on training large first-party foundation models internally, due to the high costs involved.
   • Key partners include Meta (day-one launch partner for Llama 4), Anthropic, OpenAI, and Mistral.
   • This approach allows Snowflake to integrate cutting-edge AI capabilities efficiently and provide customers with access to the world’s leading AI models.

2. Expanded Partnership with Microsoft

   • Snowflake has an expanded partnership with Microsoft to host OpenAI models on Microsoft Azure, enhancing customer choice and flexibility in leveraging AI models for enterprise applications.
   • Collaboration with Microsoft also extends to data fabric initiatives, including integration with Microsoft’s OneLake as a potential data layer for Snowflake, and embedding Cortex AI components into Microsoft Office Copilot.

3. AI-Powered Product Innovations and Integrations

   • Snowflake has integrated advanced AI models into its Cortex platform, including embedding models for document indexing and chatbots, and launched Cortex Agent to help customers scale processing of structured and unstructured data.
   • AI-powered migration enhancements have been introduced to streamline and accelerate customer migration journeys.
   • The company is focused on making Snowflake connectors available for seamless integration with platforms like Google Drive, Workday, Slack, and SharePoint, facilitating easier data access and governance.

4. Industry-Specific Collaborations

   • Snowflake has launched new automotive solutions within its AI data cloud for manufacturing, empowering companies such as CarMax and Nissan to drive innovation and efficiency.
   • Collaborations with Siemens enable unification of IT and operational technology data to optimize manufacturing processes.
   • Partnerships with organizations like Kraft Heinz and Samsung Ads demonstrate AI adoption for internal workflow automation and personalized advertising, respectively.

5. Government and Public Sector Expansion

   • Snowflake Public Sector Inc. was launched, and the company received Department of Defense Impact Level provisional authorization, positioning it to deliver mission-critical data and AI solutions to the U.S. Department of Defense and related entities.
   • Engagements with multiple government departments are ongoing, focusing on efficient data infrastructure and cross-department data sharing.

6. Upcoming Events and Further Announcements

   • Snowflake Summit, scheduled for early June, will be a major event where the company plans to reveal new capabilities and innovations supporting customers throughout their data journey.
   • Investor Day will be held in conjunction with the Summit, signaling continued strategic focus and potential announcements.

7. Go-to-Market and Sales Enablement

   • Under new leadership, Snowflake has strengthened its go-to-market rigor and sales enablement, including specialized AI-focused solution engineers ("AI ninjas") to drive AI use cases at scale.
   • The sales organization is increasingly equipped to pitch, pilot, and deploy AI solutions, reflecting a matured go-to-market motion aligned with AI developments.

Summary:
Snowflake’s strategic partnerships and collaborations for the upcoming fiscal year emphasize leveraging external AI foundation models through strong alliances with Meta, Microsoft, OpenAI, and others, rather than building large models internally. The company is integrating these models into its Cortex platform and expanding AI-powered product offerings. Industry-specific and public sector collaborations are growing, supported by new certifications and solutions. Snowflake is also enhancing its go-to-market capabilities to capitalize on AI opportunities, with significant announcements expected at the upcoming Snowflake Summit.

Cloudflare, Inc. has established multiple significant collaborations and partnerships across various sectors, demonstrating a broad and integrated approach to delivering its platform and services:

1. Government Sector Partnerships:

   • Cloudflare has won numerous SASE (Secure Access Service Edge) deals with government agencies in the US, Asia-Pacific (APAC), and Europe, including quasi-government agencies.
   • Governments worldwide are adopting Zero Trust mandates and moving away from on-premise hardware, choosing Cloudflare for its broad, integrated platform that combines security and network services.
   • Example contracts include a large US government entity signing a two-year $6.2 million Zero Trust contract and an APAC government agency signing a three-year $4.8 million contract for Magic Transit and Application Services.
   • These deals often involve partner-led motions, highlighting Cloudflare’s collaboration with channel partners to expand reach in the government sector.

2. Enterprise and Critical Infrastructure Collaborations:

   • An international critical infrastructure provider signed a seven-year $12.7 million contract, the longest duration in Cloudflare’s history, adopting the full SASE portfolio including Access, Gateway, DLP, Magic WAN, Magic Firewall, and application services.
   • A Global 2000 international business services company signed a 5.5-year $6.4 million contract for the full Zero Trust portfolio, displacing three vendors to simplify operations and improve security.
   • A Fortune 500 technology company expanded its relationship with a three-year $9.3 million contract for application services, migrating traffic from a hyperscaler to Cloudflare for better security and automation.

3. Developer Platform and AI Ecosystem Partnerships:

   • Cloudflare’s developer platform, particularly Cloudflare Workers, has been instrumental in closing large deals, including a landmark $130 million five-year contract with a leading technology company.
   • The developer speedboat team, led by Aly Cabral, actively engages with customers to build proof-of-concepts and accelerate adoption of the developer platform.
   • Cloudflare collaborates with AI companies such as Asana, Atlassian, Block, PayPal, Century, and Stripe, enabling them to build AI agent interfaces on top of Cloudflare Workers.
   • Cloudflare worked closely with Anthropic to implement the Model Context Protocol (MCP), enabling AI systems to securely connect to third-party services via Cloudflare’s network. This collaboration positions Cloudflare as a universal translator supporting multiple AI protocols, enhancing interoperability and security for AI agents.

4. Partner-First Motion:

   • Cloudflare emphasizes a partner-first approach, particularly in government deals, leveraging partnerships to drive adoption and integration of its security and network solutions.

5. Competitive Collaborations:

   • Cloudflare has been recognized by hyperscalers and competitors who refer customers to Cloudflare when their own systems cannot handle hyperscale DDoS attacks, indicating a form of indirect collaboration or acknowledgment of Cloudflare’s superior architectural capabilities.

In summary, Cloudflare’s collaborations span government agencies, large enterprises, critical infrastructure providers, AI and developer ecosystems, and channel partners. These partnerships leverage Cloudflare’s unified platform that integrates security, network performance, and developer tools, enabling customers to simplify operations, enhance security, and accelerate innovation.

Strategic Initiatives Announced by Planet Labs Regarding Satellite Services and AI Capabilities

1. Expansion and Commercialization of Satellite Services

• Landmark JSAT Partnership:

  • Planet signed a $230 million multi-year commercial agreement with JSAT, a cornerstone partner.
  • Under this deal, Planet will build, launch, and operate a constellation of 10 high-resolution Pelican satellites dedicated to JSAT’s area of interest (primarily Japan).
  • Planet retains commercial rights to sell the remaining capacity of these satellites globally, representing a significant upside opportunity.
  • This partnership is structured as a "win-win-win" for JSAT (priority access to critical intelligence), Planet (scale and monetization of strategic IP assets), and other customers (increased global capacity and potentially revised rates).
  • The satellite services market is valued in the tens of billions globally, and Planet aims to capture a meaningful portion.
  • Planet is actively pursuing similar strategic partnerships with other trusted partners across defense, intelligence, civil government, and commercial markets, leveraging all three satellite fleets (Pelican, Tanager, and Doves).
  • The company has regulatory approval for up to 32 Pelican satellites and sees typical mini-constellation deals around 10 satellites.
  • Launch timeline for JSAT satellites is mainly within the next 24 months, following priority launches for Planet’s own SkySat fleet continuity and enhancements.
  • The JSAT contract is front-end loaded in cash payments, supporting working capital and expected to be accretive to cash flow, including in fiscal 2026.
  • Planet expects to monetize the global capacity outside JSAT’s area commercially, which offers high-margin potential.

• Satellite Fleet Development:

  • In fiscal 2025, Planet launched 74 satellites, including the Second Pelican and First Tanager spacecraft.
  • Pelican 2 satellite is performing well, with multiple Pelican launches scheduled to scale towards a fully operational high-resolution fleet.
  • Tanager 1, launched last summer, is producing hyperspectral data with a five-fold improvement in tasking capacity since launch.
  • Planet is preparing to offer commercial Tanager data broadly, targeting energy and civil government verticals.
  • The company continues to invest in building and launching next-generation fleets (Pelican, Tanager, SuperDoves).

• Market Focus and Growth:

  • Planet is shifting from selling raw data to selling targeted solutions aligned with customer verticals, especially in defense and intelligence, civil government, and commercial sectors.
  • Defense and intelligence sector revenue grew over 20% year-over-year in fiscal 2025.
  • Civil government revenue grew approximately 15% year-over-year.
  • Commercial sector faced headwinds but showed signs of stabilization.
  • Planet is focusing on embedding data into core operational workflows, improving net dollar retention and average contract sizes.
  • The company is targeting growth acceleration in fiscal 2026 and beyond, supported by backlog growth and new contracts.

2. Strategic Focus on Artificial Intelligence (AI)

• AI-Enabled Solutions and Partnerships:

  • Planet released a physics-based resolution sharpening technique improving daily scan visual product usability.
  • Advanced low-touch enablement in the Planet Insights platform to automate and expand access for smaller customers.
  • Launched the first fully automated low-touch package on tropical forest observatory data for self-serve users.
  • Leveraging AI for solutions such as maritime domain awareness (MDA) and the Global Monitoring Service (GMS), which uses AI to scan entire countries or regions for changes and threats.
  • Partnered with AI leaders, notably Anthropic, to explore combining satellite data with foundation AI models.
    • Anthropic is fine-tuning its Claude model on Planet’s satellite data to enhance model accuracy.
    • This collaboration is mutually beneficial: AI unlocks value from satellite data, and satellite data helps AI models address real-world problems.
  • Planet’s unique dataset includes daily scans and a deep archive averaging over 3,000 images per location on Earth’s landmass, positioning it uniquely for AI integration.
  • AI is viewed as a strategic focus for fiscal 2026, expected to accelerate solution development and broaden accessibility to Planet’s data.
  • Near-term monetization focus is on AI-enabled solutions like maritime domain awareness, which already generates meaningful revenue and is growing.
  • Foundation model efforts with Anthropic are more experimental but hold promise for speeding time to value and expanding the customer base, including those without geospatial expertise.

• AI as a Growth Accelerant:

  • Planet sees AI as an "incredible accelerant" to delivering value and enabling new solutions.
  • AI-powered solutions, combined with new data sets and satellite services partnerships, are key drivers for growth acceleration in fiscal 2026 and beyond.
  • Investments in AI and software engineering teams are ongoing to innovate and maintain market leadership.

3. Financial and Operational Implications

• The JSAT contract and AI initiatives are expected to contribute to:
  • Revenue growth acceleration, with a goal to at least double the revenue growth rate by fiscal 2027 compared to fiscal 2026.
  • Improved gross margins, with long-term targets of 70% to 80%, supported by monetizing incremental Pelican capacity.
  • Positive adjusted EBITDA and free cash flow within the next 24 months.
  • Reduced cash burn in fiscal 2026 despite peak capital expenditures for satellite fleet expansion and AI investments.

Summary:
Planet Labs is strategically advancing its satellite services business by entering significant partnerships like the JSAT deal to build and operate dedicated satellite constellations, while commercially monetizing global capacity. Concurrently, the company is intensifying its focus on AI capabilities, partnering with leading AI firms to enhance satellite data analytics and develop AI-powered solutions such as maritime domain awareness and global monitoring. These initiatives are designed to accelerate growth, improve operational efficiency, and expand market reach across defense, civil government, and commercial sectors.

Executive Summary

This report evaluates how leading cybersecurity and software companies are integrating Artificial Intelligence (AI) into their product offerings. Across the industry, AI serves as a catalyst for innovation in threat detection, workflow automation, data analysis, and compliance. Common themes include the movement toward autonomous, agentic AI capabilities; advancements in real-time, AI-driven threat detection and response; enhanced automation for improved operational efficiency; and a focus on robust governance and compliance. Distinct company approaches reflect varying depths of AI integration, domain expertise, and ecosystem partnerships, with implications for how enterprises select and implement AI-powered cybersecurity solutions.

Introduction Purpose and Scope

The purpose of this report is to analyze the integration of AI within cybersecurity product portfolios, providing a comparative view of how various leading companies leverage AI to solve security challenges. The review focuses on real-world deployments, architectural strategies, and the business impacts of incorporating AI. Covered organizations include Asana, Inc., Accenture plc, Box, Inc., CrowdStrike Holdings, Inc., Appian Corporation, and Alphabet Inc.

Research Methodology

This analysis is based on recent earnings transcripts and public disclosures from each company, with selection criteria emphasizing active innovation in AI-driven cybersecurity solutions. Company responses were synthesized to encompass AI-enabled features, business models, technical architectures, and strategic roadmaps. The analytical framework compares implementation patterns, thematic focus areas, and differentiators across organizations.

Company Profiles and AI Capabilities Asana, Inc.

Asana embeds AI primarily through its AI Studio, which orchestrates structured and intuitive workflows that facilitate collaboration between humans and AI. The platform automates complex processes such as SAP workflow mapping, report handling, alert triaging, and vulnerability management—streamlining workload and boosting accuracy. Security and governance are front and center, with features like enterprise-grade security controls, context-aware permissions, and scalable observability. Asana’s innovative monetization relies on a tiered credit system, supporting scalable AI usage and adoption across large organizations.

Accenture plc

Accenture advances AI in cybersecurity through platforms like the Gen AI security engine in its My Security platform. This engine powers advanced threat detection and response, offering integrated data management for rapid threat identification and operational resilience. It also automates cloud migration and ensures business continuity during threat detection upgrades. These solutions augment risk visibility, safeguard sensitive assets, and deliver scalable automation in both legacy and cloud environments.

Box, Inc.

Box leverages AI agents to analyze and extract insights from unstructured content at scale, providing secure automation for due diligence, research analysis, compliance workflows, and metadata extraction. Integrations with Microsoft 365 Copilot, IBM watsonx, Google Agentspace, Salesforce, Slack, ServiceNow, and Zoom enable seamless operation across enterprise platforms. The emphasis is on security, data access controls, and compliance adherence—making Box a trusted content management and security provider, especially in regulated industries.

CrowdStrike Holdings, Inc.

CrowdStrike positions itself as an AI-native cybersecurity leader. Its Falcon platform utilizes AI at every layer, featured notably in its AI-native Security Operations Center (SOC) and generative AI security analyst, Charlotte AI, which accelerates detection, triage, and investigation. AI powers threat intelligence, adversary tracking, exposure management, and vulnerability analysis. The company requires every product team to embed AI into workflows, further using AI for customer engagement and operational automation.

Appian Corporation

Appian uses AI as an intelligent “worker” within business processes, achieving high accuracy in document classification and data extraction. With over 96% precision, their AI agents reduce manual input and quickly process large data volumes in domains like healthcare and regulatory filings. Appian’s focus is on practical, efficiency-driven applications—supported by tiered pricing and the ability for AI agents to learn and coordinate tasks throughout workflows.

Alphabet Inc.

Alphabet brings its AI expertise, including models like Gemini, to bear on cybersecurity. The company’s offerings focus on AI-powered malware detection, prioritization of cyber threats, and accelerated investigative workflows, integrated across multi-cloud and enterprise environments. Alphabet’s broader strategy is to embed advanced AI capabilities throughout its security solutions, benefiting from continuous model improvement and research.

Comparative Thematic Analysis Threat Detection and Response

Companies like CrowdStrike and Accenture lead in embedding AI for real-time, advanced threat detection and automated response. CrowdStrike’s Charlotte AI acts as a generative analyst, while Accenture’s platforms offer seamless threat identification and cloud migration security.

Workflow Automation and Efficiency

Asana, Appian, and Box focus on AI-driven automation to orchestrate tasks and reduce manual effort. Asana’s workflows, Appian’s precision in document processing, and Box’s broad unstructured data automation are examples of how AI powers operational efficiencies.

AI Agents and Autonomous Capabilities

Agentic AI is emerging rapidly. Asana and CrowdStrike are developing autonomous capabilities for decomposing complex security campaigns, while Box and Appian deploy AI agents that learn, act, and coordinate across workflows with human oversight where necessary.

Data and Content Analysis

Box excels in analyzing unstructured content, leveraging AI for deep research, trend correlation, and compliance tasks. Appian and Alphabet focus on domain-specific analytics and high-accuracy data extraction for regulatory and investigative use cases.

Security, Governance, and Compliance

All reviewed companies emphasize enterprise-grade security controls, with robust access management and compliance. Asana and Box, serving regulated industries, highlight granular observability and auditability, while Alphabet and CrowdStrike integrate these controls at the platform level.

Integration and Ecosystem Partnerships

Box demonstrates extensive third-party integration with major enterprise platforms. Accenture and Alphabet expand multi-cloud, platform-wide support, while Asana and Appian build interoperability into their foundational architectures.

Technology Architecture and Platforms Core AI Models and Algorithms

• Asana: Proprietary work graph and orchestration algorithms govern collaborative AI workflows.
• Accenture: Gen AI security engine and integrated enterprise models fuel detection and automation.
• Box: AI agents leverage NLP and content extraction models, integrated with Microsoft, IBM, Google APIs.
• CrowdStrike: Generative AI and proprietary threat analysis models (e.g., Charlotte AI) operate across the Falcon platform.
• Appian: Embedded AI “workers” process documents with high-accuracy machine learning models.
• Alphabet: Leads with Gemini and other advanced models for malware detection and threat analytics.

Platform Infrastructure

The infrastructure backbone ranges from Asana’s scalable work graphs and granular permission systems to Box’s multi-platform content pipelines and Appian’s auditable workflow engine. CrowdStrike’s modular architecture allows rapid AI module deployment; Alphabet builds upon its robust, multi-cloud security stack.

Business Models and Monetization Pricing and Licensing Structures

• Asana: Tiered credit system decouples AI consumption from seat-based licensing, supporting variable-scale adoption.
• Accenture: Service/platform-driven contracts incorporate AI as value-added capability.
• Box: AI features bundled into existing or premium compliance offerings; integrations with partner platforms.
• CrowdStrike: Subscription-based modules, each supported by AI-driven feature sets with clear ARR metrics.
• Appian: Tiered pricing for AI-inclusive plans; demonstrable rapid growth in revenue from AI-enabled tiers.
• Alphabet: Likely bundled or usage-based pricing for AI security enhancements within cloud portfolios.

Scalability and ROI Metrics

Companies measure AI impact by adoption rates, cost savings, automation-driven productivity gains, and revenue growth from AI-driven products. Notably, Appian and CrowdStrike cite significant increases in revenue and efficiency attributable to AI, while Asana supports large-scale, flexible adoption models.

Future Outlook and Emerging Trends

The future of AI in cybersecurity centers on:

• Autonomous, agentic AI capable of both orchestrating and executing complex tasks with minimal human intervention.
• Expanded integration across SaaS, multi-cloud, and hybrid environments.
• Enhanced cross-platform AI ecosystems, fostering open, interoperable AI applications.
• Growing importance of compliance, auditability, and explainability in AI-driven decisions amidst evolving threats.

Conclusion and Recommendations

AI is transforming cybersecurity from reactive defense to proactive, automated resilience. Enterprises should:

• Prioritize vendors with demonstrable AI-driven automation, agentic capabilities, and robust governance frameworks.
• Embrace open and interoperable solutions to capitalize on evolving AI ecosystems.
• Continually assess and monitor ROI for AI adoption, focusing on both efficiency gains and security enhancement.
• Maintain a “human-in-the-loop” model—especially for high-stakes threat or compliance decisions—while progressively exploring autonomous functionality for scalable security management.

Selecting platforms aligning with organizational needs and partnering with companies at the forefront of AI-enabled cybersecurity will be critical for sustaining protection in an increasingly complex digital landscape.

Fortinet is actively leveraging AI technologies to enhance its financial services and operational efficiency, as detailed in the latest quarter's earnings transcript:

AI Integration and Product Development

• Fortinet has been investing in AI capabilities for over 15 years and currently holds over 500 issued and pending AI patents, more than any competitor.
• AI technology is integrated into a dozen products, including:
  • FortiAI Assist: Automates security tasks.
  • FortiAI Protect: Provides advanced threat detection.
  • FortiAI Secure AI: Protects AI infrastructure.
• These AI-driven solutions contribute to operational efficiency by automating complex security operations and enhancing threat detection capabilities.

Financial Impact and Growth Drivers

• AI-driven SecOps billings grew by 29%, now accounting for 10% of total billings, indicating strong market adoption and revenue contribution.
• Total billings grew 14% to $1.6 billion, with AI-driven SecOps and unified SASE showing significant growth (29% and 18%, respectively).
• The integration of AI into Fortinet’s security fabric helps customers consolidate multiple security vendors, reducing complexity and operational costs.

Product Performance and Efficiency

• The newly announced FortiGate 700G series firewall, powered by FortiASIC technology, delivers a 5 to 10x performance advantage over competitors, lowering total cost of ownership and energy consumption.
• FortiOS, the operating system underpinning Fortinet’s products, is recognized across five Gartner Magic Quadrants, providing a unified platform that enhances operational efficiency.
• AI capabilities embedded in FortiOS and FortiASIC technology enable seamless integration of networking and security functions, improving user experience and reducing operational complexity.

Market Position and Strategic Focus

• Fortinet expects AI and OT security to be key growth drivers over the next five years, supported by strategic investments and specialized solutions.
• The company’s AI-enhanced Forti Fabric solution is driving strong growth in secure operations, with customers increasingly adopting integrated AI solutions for cybersecurity.
• Fortinet’s AI strategy supports its leadership in secure networking, SD-WAN, OT security, and SASE markets, positioning it for continued market share gains.

Summary

Fortinet is leveraging AI technologies extensively to automate security operations, enhance threat detection, and protect AI infrastructure, which in turn drives strong revenue growth and operational efficiencies. The integration of AI into its product portfolio, combined with proprietary ASIC technology and a unified operating system, enables Fortinet to offer high-performance, cost-effective, and scalable security solutions that meet evolving customer needs in financial services and beyond.