Accelerate Productivity in 2025

Reignite Growth Despite the Global Slowdown

Executive Summary

 

The Evolution and Drivers of Product Development

The Changing Landscape of Product Development

In 2022, global research and development expenditure reached about USD 3.1 trillion, with the top 8 regions accounting for roughly 82% of that total. The USA led with about 30% of global R&D, followed by China at 27%.

In terms of innovation intensity, nations such as Israel, Korea, and the USA exceed 3% of gross domestic product (GDP) in R&D investment.

 

 

This surge in investment aligns with intellectual property creation, with 3.55 million patent applications filed globally in 2023. Further, Switzerland ranked first, followed by Sweden, the USA, Singapore, and the UK in the 2024 Global Innovation Index (GII), which assesses R&D, talent, infrastructure, and outputs like patents and technology use.

Forces Reshaping Global Product Development

By 2024, 4.28 million robots were operating in factories globally, a 10% increase from the prior year. Moreover, more than half a million new installations have been added annually for three years in a row.

Likewise, in the same year, 23% of surveyed product and development respondents said they regularly use generative AI in at least one business function.

Moreover, manufacturers are shifting from selling products to offering product-as-a-service (PaaS) models. Also, companies use IoT sensors and digital twins to track real-world performance, predict maintenance, and refine designs after launch.

This approach supports product-service systems (PSS) that merge physical goods with digital services to offer continuous value and lifecycle sustainability.

Product development is undergoing a transformation driven by AI integration, digital connectivity, and sustainable engineering. These shifts redefine innovation speed, collaboration, and lifecycle intelligence.

The following sections outline the top product development trends to watch in 2026 and beyond while highlighting how emerging technologies are setting new benchmarks for efficiency and creativity..

1. Generative AI Integration & AI-Augmented Design

Generative AI is embedded in product development workflows end-to-end. 33% of respondents of a McKinsey survey expect no change in headcount, while 34% foresee workforce growth due to generative AI integration. This aligns with broader enterprise trends where AI copilots, design generators, and automated prototyping tools accelerate concept-to-launch cycles.

 

 

Additionally, 28% of organizations are already using generative AI in product development to make it the second most common use case after marketing and sales.

 

 

Moreover, generative AI is now being used to compress product development timelines. In physical product development, cycle times have shrunk by as much as 70% in some instances when AI tools are applied across concept, prototyping, and iteration phases.

Likewise, product managers using generative AI tools achieved a 5% faster time to market over a full development cycle, while their productivity on routine tasks rose by 40%.

Beyond individual roles, AI tools bridge traditional silos within design, product, and engineering by enabling shared artifacts, like sketches, prompts, generated prototypes, and flow between roles. This lowers the barriers to cross-functional collaboration and offers faster decisions on scope, features, or design trade-offs.

Meanwhile, a tool like IBM’s watsonx includes features for code assistants that claim a 30% reduction in development effort or productivity gains at that scale when used in enterprise settings.

2. Data & BI-Driven Decisions

User data, such as net promoter score (NPS), retention rate, and churn rate, is essential to understanding customer satisfaction and loyalty. A/B testing improves onboarding completion by 22% when friction points are identified and addressed.

Similarly, product data, including bounce rates and heatmaps, identifies feature adoption and drop-off zones. In one case, usage data revealed that over 60% of active users engaged daily with a specific feature to prompt deeper investment in that area.

Additionally, treating data as a product (DaaP) transforms raw datasets into structured, accessible, and valuable assets. For instance, customer insights platforms aggregate data from in-store purchases, online behavior, and social media to create comprehensive profiles. These platforms rely on APIs, documentation, and performance indicators to deliver actionable insights.

Further, advanced analytics and BI tools empower product managers to identify patterns, trends, and customer behaviors. Predictive modeling and machine learning algorithms forecast churn, simulate product launch scenarios, and optimize pricing strategies.

Moreover, data-driven roadmaps prioritize features based on customer needs, revenue potential, and feasibility. Metrics such as daily active users (DAU), customer acquisition cost (CAC), and customer lifetime value (CLV) guide strategic planning.

For example, churn among Android users dropped by 18% after resolving technical issues identified through retention curves and segment data. Roadmaps also align development efforts with broader company goals, translating technical tasks into business impact for stakeholders.

3. IoT and Connectivity & Smart Products

IoT and smart connectivity enhance the process of product development with embedded intelligence, predictive capabilities, and data-driven design strategies.

The global IoT in product development market was valued at USD 48.5 billion in 2025 and is projected to reach USD 187.6 billion by 2035 at a CAGR of 14.5%. This growth is driven by the integration of smart sensors, edge computing, and AI into product design workflows.

 

 

In fact, 99% of companies surveyed have either implemented or are piloting product connectivity, with 48% increasing their annual spend on IoT initiatives. These investments enable real-time monitoring, predictive maintenance, and remote diagnostics as standard features in industrial and consumer products.

Additionally, 75% of companies report that product connectivity supports outcome-based pricing and as-a-service models. For example, Hitachi’s Lumada platform connects industrial machinery and IT systems to deliver global services.

In logistics, connected truck and trailer systems have saved mid-size transport companies up to EUR 876 000 annually, which represents 6% of total spend. These models rely on real-time data streams and AI-driven analytics to optimize performance and reduce operational costs.

Design and engineering services lead the IoT product development landscape. Companies invest in low-power sensors, microcontrollers, and firmware that support secure communication and interoperability.

OTA firmware updates allow manufacturers to expand product features post-deployment. Also, prototyping and manufacturing support with simulation software and digital twins accelerate time-to-market and improve product reliability.

4. Advanced Prototyping & Digital Twins

Digital twins are becoming central to smart product development. These virtual models simulate real-world behavior, allowing teams to run what-if scenarios, predict future performance, and validate configurations before physical production.

Companies using digital twins reduced development time by 20-50%, cut physical prototyping from three iterations to one, and achieved 25% fewer quality issues at launch. Additionally, products developed with digital twins have seen a 3-5% increase in sales due to better features and customer satisfaction.

With this, AI-driven product carbon footprint (PCF) tools and automation enable businesses to track emissions, improve transparency, boost recycling and circularity, and optimize energy and asset management.

Similarly, early-stage prototyping reduces risk and cost by allowing teams to test assumptions, gather feedback, and iterate quickly. Figma leads the collaborative prototyping tool market with a 31.42% share, followed by Adobe XD at 10.21%.

Likewise, hardware prototyping platforms like Arduino and Raspberry Pi simulate product logic and test connected device behavior. For physical products, computer-aided designs (CAD) tools support precise modeling and simulation to refine form, fit, and function before fabrication begins.

Also, 3D printing and computer numerical control (CNC) machining shorten development cycles, improve accuracy, and reduce product waste. For instance, 3D printing enables functional prototypes and tooling production to reduce material waste by up to 90%. Meanwhile, modern CNC machining systems achieve tolerances within 0.001 inch and can run 24/7 with automated toolpath generation directly from CAD models.

5. Packaging & Commercial Presentation

Packaging and presentation influence consumer perception, logistics, sustainability, and brand equity. 58% of global shoppers actively avoid products with excessive packaging due to environmental concerns. Thus, brands shift toward biodegradable, recyclable, and reusable materials to meet expectations.

Moreover, digital design tools and visual storytelling convey product value and brand identity. Packaging design based on digital visual communication enhances consumer engagement and brand recall, especially when integrated with interactive elements and personalized aesthetics.

Further, smart packaging integrates QR codes, near-field communication (NFC) chips, and augmented reality (AR) overlays to transform static boxes into interactive touchpoints and increase user engagement and brand storytelling. Moreover, packaging designs are shifting toward bold, playful visuals and strong typographic elements to emphasize curated frames, lively color palettes, and personality-driven aesthetics for capturing attention at the shelf and online.

Also, emerging brands are adding easy-open, reclose, and dispensing innovations to set themselves apart in a crowded shelf environment and improve consumer convenience and perceived premium quality. These mechanical features often tie into brand differentiation and justify higher price points.

Additionally, digital tools are being used to optimize logo placement and visual saliency. For instance, deep learning models evaluate how packaging layout drives attention and brand visibility while helping design teams refine packaging for maximum eye capture.

 

 

6. User-Centric & Outcome-Driven Mindset

Products developed with a user-centered design process can increase user satisfaction by up to 30% compared to conventional design practices. In addition, companies that increase their UX budget by 10% often realize an 83% increase in conversion rates. With such returns, 77.3% of brands consider customer experience (CX) a key competitive differentiator. Moreover, 88% of users say they won’t return to a site after a bad user experience.

Further, building on user-centric thinking, the outcome-driven mindset shifts focus from delivering outputs, like features, reports, and tasks, toward achieving measurable impacts, like behavioral change, user benefit, and business value.

Moreover, outcome-driven thinking aligns work with purpose, builds empathy by uncovering real needs, and builds collaboration through shared understanding. This is tracked via metrics like user adoption rate, task completion rate, net promoter score (NPS), or customer lifetime value.

 

 

Additionally, in 2025, TSIA’s benchmarking data revealed a 6% increase in companies following an adoption framework telemetry similar to NPS. Likewise, in the advertising and media space, campaigns using attention-based outcome metrics achieved on average 41% higher brand lift and 55% stronger lower-funnel impact than less outcome-oriented campaigns.

7. Sustainability, Ethical & Circular Design

A product’s design determines up to 80% of its environmental impact, which makes early-stage decisions critical for long-term sustainability.

 

 

Likewise, a comprehensive review identified 297 sustainable product design (SPD) factors, with 132 environmental, 96 social, and 69 economic considerations mapped across the product life cycle. For instance, material consumption and energy use were cited in 24 and 22 studies, respectively, while recyclability and reusability appeared in 20 and 16 studies. These factors directly influence resource efficiency, waste reduction, and circularity.

Additionally, companies are beginning to act. One industrial manufacturer collaborated with ocean clean-up campaigns to convert plastic waste into recycled polymer fibers for vehicle seat covers. Another medical device firm prioritized sustainable design by eliminating single-use devices and partnering with environmental organizations to enhance product innovation.

To operationalize sustainable design, Boston Consulting Group proposes six strategies: dematerialization, next-best material selection, green supply chains, longevity, product efficiency, and circularity.

 

 

For example, switching to lightweight composite materials reduces vehicle energy consumption by 50%, while remanufacturing components consumes significantly less energy than producing new ones.

8. Localization, Resilience & Nearshoring

As companies expand into international markets, product localization becomes essential for translation, adapting UX, pricing, payment systems, and cultural norms. For example, 60% of non-native English speakers rarely or never buy from English-only websites, and only 18% of European internet users are willing to purchase from sites in foreign languages.

Moreover, software-as-a-service (SaaS) platforms like Lucidchart offer onboarding in 12 languages, while Paxful supports 49 languages across its product, marketing, and support channels.

Similarly, resilience in product development links to supply chain strategy. 66% of US companies are increasing domestic manufacturing, while 53% are adopting nearshoring within North America.

 

 

This shift is driven by the need to reduce lead times, improve quality control, and mitigate risks from geopolitical tensions and pandemics. For instance, Boeing is nearshoring operations to Mexico to reduce cultural issues.

Additionally, the total cost of ownership (TCO) model reveals that transport costs, while not the largest component, affect lead times and inventory costs. A study comparing production in China, North Macedonia, Poland, and Benelux found that North Macedonia consistently offered the lowest TCO, with savings driven by reduced wages and shorter transport distances.

Also, digital integration is crucial for managing dispersed supply chains. Real-time tracking, collaborative inventory planning, and visibility into tier-two and tier-three suppliers enable faster, data-driven decisions.

9. Agile Phase Gate Integration

Agile phase-gate or agile-stage-gate hybrid combines the structured, gated phase model of traditional product development with the flexibility and iteration of agile methods. The stage-gate or phase-gate processes enforce control, resource allocation, and risk checkpoints, while Agile methods like sprints, backlogs, and evolving requirements permit responsiveness to change.

Firms embed agile practices within stage-gate stages, especially in development and testing phases, to gain faster release cycles and better responsiveness. For instance, in an evaluation of three manufacturing SMEs using agile-stage-gate, results included shorter time to market, higher new product process effectiveness, and better project success rates.

In another multi-case study of seven technology firms, hybrid approaches combining stage-gate at strategic levels and Scrum in execution were shown to reduce process complexity and improve performance compared to pure stage-gate improvements. With that, agile-stage-gate models report 25% less work effort per project and a 20% reduction in rework.

As hybrid models require adaptation, research also highlights how often they are tailored. Agile is the most integrated methodology, with design thinking and lean startup also being combined.

Further, it model is categorized into two hybrid structures – nested hybridization (one or more methodologies are integrated within the stages) and handed-over hybridization (one methodology is implemented before or after the Stage-Gate process).

10. Organizational & Role Evolution

A modern product manager now straddles multiple domains: approximately 80% of product managers actively contribute to design decisions, 80% participate in go-to-market planning, and about 50% engage in pricing strategies. Moreover, 60% possess foundational analytics skills to derive insights independently without relying fully on analytics teams.

 

 

Likewise, product managers allocate their time across multiple functions, by spending 18% on defining product strategy, 15% collaborating with technical and design teams, and 14% defining product requirements.

To enable this shift, organizations are evolving structures toward empowerment and accountability. Effective empowerment blends autonomy with clear guardrails and support systems. Such a balance allows workers to execute independently within aligned objectives for every product department.

Meanwhile, optimization of workflows embeds a meaningful impact to emphasize redesigning how work flows, rather than just flattening hierarchies or removing layers. Through workflow redesign, product teams reduce friction, shorten decision cycles, and improve throughput in iterative development.

Similarly, in the consumer-goods and retail intersection, product roles require deeper customer insight acumen. Product leaders are urged to understand shifting consumer habits, digital touchpoints, and omnichannel behavior to deliver seamless interactions. This demand pushes product roles to blend technical, design, and market expertise more tightly.

Strategic Implications for Business Leaders

Product development demands adaptive, data-driven roadmaps while shifting from static planning to continuous iteration based on real-time performance insights. Investing in AI-powered PLM is essential as modern PLM platforms combine design, engineering, and sustainability data, enabling faster decisions and automated change management.

Moreover, sustainable advantage comes from embedding circularity and lifecycle intelligence directly into design systems to allow real-time tracking of material reuse, carbon footprint, and energy performance. Teams must be upskilled for AI-augmented collaboration, with engineers supervising and refining AI-generated outputs.

  • Integrate generative design, simulation, and supply data in one platform to cut design-to-production cycles while improving traceability and regulatory compliance.
  • Use high-fidelity digital twins to simulate real-world performance for enabling predictive maintenance and design iteration in near real time in sectors like mobility, aerospace, and energy.
  • Deploy PLM-embedded sustainability modules to automatically calculate product carbon intensity, water use, and recyclability scores at every design stage.
  • Link IoT and usage data from deployed products directly back into R&D pipelines to enable post-launch design refinement and AI-assisted feature evolution.
  • Upskill engineers in prompt-based design, ML-driven simulation, and AI model governance so human expertise remains central while leveraging automation efficiency.

Explore the Latest Product Development Trends to Stay Ahead

Rapid advances in AI, connectivity, and automation are redefining product development worldwide. The next phase of growth focuses on intelligent design systems, adaptive digital twins, and integrated data ecosystems that enable faster innovation, sustainable engineering, and continuous lifecycle optimization.

With access to over 9 million emerging companies and 20K+ technologies & trends globally, our AI and Big Data-powered Discovery Platform equips you with the actionable insights you need to stay ahead of the curve in your market.

By leveraging this platform, anticipate regional shifts, capture growth in frontier markets, and invest confidently in the industries that will define the next decade. Stay prepared, resilient, and positioned to lead in 2026 and beyond.