AI Coverage from ArrowflyAI for Engineers Research
The 2027 Outlook of AI in Engineering
Engineering organizations are investing in AI by function. But how far along are they really? What is working, what is not, and what do engineering leaders expect by 2030? The 2027 Outlook of AI is an original research study designed to answer those questions across five engineering disciplines.
Conducted by the Arrowfly editorial team and AI Advisory Board, the study benchmarks how the industry is adopting AI across design, MedTech, robotics, energy, and industrial operations. Results will be published as a series of five gated research reports in 2027.
What the Research Covers
Five discipline-specific reports
Each report is grounded in survey data from working engineers and technical leaders.
The Future of AI in Engineering Design and Simulation
How engineering leaders are moving from AI experimentation to accelerated design, simulation, and product innovation.
Key areas: Generative design, AI-enabled CAE, digital twins, engineering copilots, and the workflows most likely to be reshaped by 2030.
The Future of AI in Medical Devices and MedTech
Balancing innovation, clinical evidence, regulatory readiness, and patient trust.
Key areas: AI applications in diagnostics, imaging, wearables, and robotics, clinical and regulatory obstacles, and AI’s role in future product development.
The Future of AI in Robotics and Automation
From intelligent automation to scalable autonomy across factories, warehouses, and beyond.
Key areas: Investment priorities for cobots, AMRs, computer vision, and edge AI, along with executive expectations for autonomy by 2030.
The Future of AI in Energy and Electronics
The next era of intelligent energy systems, EVs, semiconductors, and embedded intelligence.
Key areas: AI’s role in battery management, grid intelligence, power systems, and energy optimization, plus edge-versus-cloud deployment priorities.
The Future of AI in Industrial Operations and Smart Manufacturing
How industrial leaders are using AI to improve uptime, quality, throughput, and operational resilience.
Key areas: Predictive maintenance, quality inspection, supply chain optimization, digital twins, and the challenge of scaling from pilot to plant-wide deployment.
Participate in the Research
Share your organization’s perspective on AI in engineering
Survey participants contribute to one of the most comprehensive studies of AI adoption across engineering disciplines, and your input helps shape the findings the industry will use to plan, invest, and build.
Engineers who complete the survey and qualify will receive a complimentary pass to AI for Engineers, September 20–22, 2027, at M Resort Spa & Casino, Henderson, right outside of Las Vegas.
Surveys open Q4 2026