Curated Measure
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AI Investment Barometer

Last updated Feb 2, 2026 4 series in this Curated Measure

At a glance:

Tracks how often companies discuss AI in the context of spending commitments during earnings calls.

Coverage

Public firms, 80+ countries, 2002-present.

Methodology and data

Granularity

Earnings-call level (firm-panel export: one row per call).

Source

LSEG earnings-call transcripts (English).

Update schedule
Last updated Feb 2, 2026. Update frequency:

Quarterly

Export shape

Time-series aggregates; firm-panel call-level rows.

Access

Free preview; exports depend on plan.

Access details Pricing

Overview

Explore the data

This measure includes 4 related series. Select a series to update the chart and compare definitions via Details.

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over time

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Mean number of sentences per earnings call containing a query keyword.

How to read this chart

This time-series chart shows the mean number of sentences per earnings call containing a query keyword.

Interpretation:

  • Higher values mean call participants devoted more discussion to the topic.
  • The chart is best for timing and directional monitoring.
  • Use exports for statistical modeling, replication, and firm-level analysis.

How to access?

Preview: Browse all series and view charts without an account. Downloads require sign-in .

Free plan

  • series: time-series + panel included.
  • Other series: 1 unlocks panel + time-series.

Standard plan

  • Time-series: included for all series.
  • Panel: series included; other series require 1 panel export credit .

Research / Enterprise

  • Time-series: included for all series.
  • Panel: included for all series.

Methodology and data

Overview

Our AI Investment Barometer measures corporate focus on artificial intelligence investments by analyzing earnings call transcripts. It identifies passages where AI-related topics are discussed in an investment context, providing insight into how companies are allocating resources toward AI capabilities.

Methodology

AI Mentions

Our AI keyword taxonomy captures references to artificial intelligence across multiple dimensions:

  • Core terminology — foundational concepts such as artificial intelligence, machine learning, deep learning, generative AI, and large language models
  • Technical concepts — terms frequently discussed in business contexts, including neural networks, natural language processing, computer vision, foundation models, and inference
  • Application-layer terms — language signaling AI deployment, such as chatbots, intelligent automation, predictive maintenance, and AI-powered capabilities
  • Model names and versions — specific products from leading AI providers, including OpenAI (GPT-4, GPT-5, o1, o3), Anthropic (Claude 3.5, Claude 4, Claude 4.5), Google (Gemini 2, Gemini 3, Gemma), Meta (Llama 3, Llama 4), and Mistral (Mistral Large, Mixtral, Codestral)
  • Platforms and tools — enterprise AI infrastructure through which companies access AI capabilities, such as Microsoft Copilot, Amazon Bedrock, Azure OpenAI, Google Vertex AI, Databricks, and Hugging Face

This multi-layered approach captures both strategic AI discussions and specific technology adoption signals. The keyword list requires periodic updates to reflect the rapidly evolving model landscape.

Investment Keywords

Our investment keyword taxonomy captures corporate spending commitments across two dimensions:

  • Capital expenditure (Capex) — terms identifying infrastructure and fixed-asset investments, including capital expenditure, capital spending, equipment investment, infrastructure spending, and capital budgeting
  • Research & Development (R&D) — terms capturing innovation-oriented investments by combining core concepts (R&D, research, product development, innovation, patents) with spending-related language (investment, expense, expenditure, cost)

Combined Signal

The AI Investment Signal is constructed by identifying earnings call passages where AI keywords co-occur with investment keywords. This approach naturally captures AI-specific investment discussions—such as GPU spending, data center investment, or compute expenditure—by leveraging the intersection of both taxonomies, rather than requiring a separate keyword category for AI infrastructure.

Data Access

Download access to the data requires paid export credits on a Free or Standard plan; it is included in the Research plan.

See our pricing page for more details.

  • Format: CSV
  • Frequency: Updated bi-weekly
  • Coverage: 14,000+ global companies, 2017-present

References

NL Analytics. (2026). AI Investment Barometer [Data set]. NL Analytics. https://apps.nlanalytics.tech/curated-measures/ai-investment-barometer/