PitchBook-新兴技术未来报告：世代人工智能（英）-2023.4-33页_486kb

Emerging Tech Future Report: Generative AI Transformation by PitchBook

This report examines how Generative AI (GenAI), particularly Large Language Models (LLMs), is reshaping key emerging technology sectors, with focus on near-term applications and long-term implications. Authored by PitchBook's Emerging Tech Research team.

Introduction

The maturation of transformer-trained LLMs, exemplified by ChatGPT, is driving broad industry impacts, enhancing accessibility and productivity. It presents both opportunities and challenges, including privacy, security, regulation, and ethical concerns. The report analyzes various sectors, noting a transition from digital transformation to AI-native operations.

Mobility Tech

Near-term applications

• Enhance infotainment systems and automotive software through conversational interfaces.
• Improve transit routing and ridehailing experiences.

Long-term implications

• Accelerate product design and manufacturing optimization.
• Foster conversational mobility services, potentially transforming user interactions.

Supply Chain Tech

Near-term applications

• Optimize data queries, order tracking, and scheduling for improved productivity.

Long-term implications

• Require incentives for data openness; automation could turbocharge logistics but faces siloed data barriers, potentially boosting third-party logistics efficiency.

E-commerce

Near-term applications

• automate product descriptions, listings, and customer support via chatbots and plugins.
• Enhance individualized shopping through plugins and personalized content.

Long-term implications

• Scalable personalization in B2B e-commerce; litigation risks and consumer data privacy concerns may slow adoption; could lead to hyper-personalization and new market dynamics.

Fintech

Near-term applications

• Automate data processing tasks like document handling and scenario analysis for portfolio management.
• Enhance marketing with tailored ads and improve sales workflows through AI assistants.

Long-term implications

• Embed AI into financial products for competitive advantage; drive personalized recommendations but face regulatory hurdles; risk triggering price transparency and ethical scrutiny.

Healthcare IT

Near-term applications

• Enable cost-effective clinical documentation through ambient AI, integrate into EHR workflows.
• Accelerate prior authorization submissions and revenue cycle tasks.

Long-term implications

• Cautious adoption due to trust gaps in clinical decisions; prioritize revenue cycle automation with careful patient outcome consideration; hindered by legacy infrastructure.

Digital Health

Near-term applications

• Support care management and symptom checkers, improved via generative AI.
• Provide companionship and digital therapy through chatbots, enhancing mental health access.

Long-term implications

• Integrate with digital twins for personalized medicine and accurate diagnoses; face reimbursement and liability challenges, progressing slowly.

Gaming

Near-term applications

• Expedite game prototyping with AI-generated art and UGC creation; assist with dialogue and coding.
• Benefit small studios through efficient resource use and enhanced user experiences.

Long-term implications

• Manage expectations for AI limitations; address creative displacement concerns; mitigate toxicity and ethical oversight issues as AI integrates deeper.

Agtech

Near-term applications

• Apply AI to crop disease diagnosis, yield prediction, and precision agriculture tasks.
• Monitor livestock health and optimize resource use.

Long-term implications

• Boost farmer efficiency and economic growth, particularly in developing regions; create new jobs but aid sustainable practices through resource optimization.

Foodtech

Near-term applications

• Generate recipe suggestions and optimize menus based on preferences and inventory.
• Streamline shopping lists and order fulfillment for food service.

Long-term implications

• Achieve hyper-personalization in food offerings; reduce waste through better demand forecasting; enhance customer experiences while adapting to workforce changes.

Climate Tech

Near-term applications

• Provide bespoke carbon emission reduction guidance; assess carbon offset quality.
• Optimize green construction and energy efficiency in designs.

Long-term implications

• Energy consumption concerns from AI training pose carbon risks; focus on halving gen AI's footprint through efficient hardware; balance emissions reductions with computational needs.

Enterprise SaaS

Near-term applications

• Generate content drafts, such as reports and communications, to save time.
• Enhance enterprise search and customer service through AI interfaces.

Long-term implications

• Leverage AI for personalized virtual humans in marketing and support; mitigate risks of hallucinations and misinformation; raise concerns about data monopolization.

AI & ML

Near-term applications

• Develop tools for foundation model customization and vector search to support AI-native workflows.
• Enable agentic AI for automation and learning from user actions.

Long-term implications

• Extend to generative media, creating more efficient creative processes; foster software as a service evolution through predictive capabilities.

Infosec

Near-term applications

• Automate security data analysis, penetration testing, and compliance documentation.
• Streamline identity governance and secure coding processes.

Long-term implications

• Disrupt traditional SIEM industries; empower users with AI tools for threat detection; enable self-patching security systems.

IoT

Near-term applications

• Enhance connected vehicles and industrial documentation query responses.
• Improve video surveillance analytics and voice synthesis for smart home integration.

Long-term implications

• Transform industrial design and facilitate digital twins with natural language; bridge IT/OT divides through accessible AI tools.

Crypto/Web3

Near-term applications

• Aid smart contract development, auditing, and querying blockchain data.
• Generate crypto protocol documentation and analyze market trends.

Long-term implications

• Enable decentralized AI infrastructure and tokenization of digital assets; but risk amplifying scams and security vulnerabilities.

Insurtech

Near-term applications

• Enhance chatbots for personalized CS, risk assessment, and claims processing; improve accuracy in underwriting and claims evaluation.

Long-term implications

• Adoption may be slow due to regulatory and ethical risks; potential for straight-through processing could cut costs; new insurance products needed to address unintended damages from AI.