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HalliburtonLinkedIn

Halliburton CTO discusses using AI to manage uncertainty and improve decision-making in E&P.

Source

LinkedInAug 11, 2026
likes
217
comments
12

Post

Every measurement, interpretation, and forecast carries uncertainty. The challenge is not eliminating uncertainty. It is understanding it and using it to make better decisions. In this blog, based on insights shared during a Reuters Data Driven Oil & Gas USA panel discussion, Shaun Baker, chief technology officer and head of software engineering for Halliburton Landmark, discusses how artificial intelligence can help exploration and production organizations uncover value from existing data and focus on the decisions that matter most. Read the blog to learn how leading organizations are turning data complexity into decision advantage >> https://lnkd.in/g82fukPk

linkedin.com/posts/halliburton_every-measurement-interpretation-and-f...Read the full source

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From the Signal API record
Signal
LinkedIn

What this signalsCompany posts often show what the team is pushing right now.

The full record

From the Signal API record

Topics and mentions

Tags

  • Data Science
  • Artificial Intelligence
  • Analytics & Insights
  • Oil & Gas
  • Operations

Initiatives

  • using artificial intelligence to uncover value from data
  • improving decision-making by understanding uncertainty

Pain points

  • uncertainty in measurements, interpretations, and forecasts
  • data complexity

Competitors named

  • Reuters

Extraction

Detected
Aug 13, 2026
signal_type
linkedin-post-company
signal_subtype
linkedinPost

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This page shows a preview. The full linkedin-post-company record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.

Company

  • linkedin_urlValue in the API
  • industriesValue in the API
  • employee_count_lowValue in the API
  • employee_count_highValue in the API
  • revenueValue in the API
  • descriptionValue in the API

Signal

  • signal_nameValue in the API
  • associationValue in the API
Show the full JSONThe record on this page and the API request

GET /v1/signals/e9c5ec28-9bd6-4946-a819-6ef34b6a9a46 returns this record as JSON. POST /v1/companies/enrich returns every signal for halliburton.com.

{
  "signal_id": "e9c5ec28-9bd6-4946-a819-6ef34b6a9a46",
  "signal_type": "linkedin-post-company",
  "signal_subtype": "linkedinPost",
  "detected_at": "2026-08-13T15:58:08.486+00:00",
  "company": {
    "name": "Halliburton",
    "domain": "halliburton.com"
  },
  "data": {
    "tags": [
      "Data Science",
      "Artificial Intelligence",
      "Analytics & Insights",
      "Oil & Gas",
      "Operations"
    ],
    "summary": "Halliburton CTO discusses using AI to manage uncertainty and improve decision-making in E&P.",
    "post_url": "https://www.linkedin.com/posts/halliburton_every-measurement-interpretation-and-forecast-activity-7492916494985490432-zGjJ",
    "num_likes": 217,
    "post_text": "Every measurement, interpretation, and forecast carries uncertainty.\n\nThe challenge is not eliminating uncertainty. It is understanding it and using it to make better decisions.\n\nIn this blog, based on insights shared during a Reuters Data Driven Oil & Gas USA panel discussion, Shaun Baker, chief technology officer and head of software engineering for Halliburton Landmark, discusses how artificial intelligence can help exploration and production organizations uncover value from existing data and focus on the decisions that matter most.\n\nRead the blog to learn how leading organizations are turning data complexity into decision advantage >> https://lnkd.in/g82fukPk",
    "initiatives": [
      {
        "topic": "using artificial intelligence to uncover value from data",
        "urgency": 0.6
      },
      {
        "topic": "improving decision-making by understanding uncertainty",
        "urgency": 0.7
      }
    ],
    "pain_points": [
      {
        "topic": "uncertainty in measurements, interpretations, and forecasts",
        "intensity": 0.5
      },
      {
        "topic": "data complexity",
        "intensity": 0.4
      }
    ],
    "posted_date": "2026-08-11T12:15:04.061Z",
    "num_comments": 12,
    "competitors_mentioned": [
      {
        "name": "Reuters"
      }
    ],
    "technologies_mentioned": [
      {
        "name": "Artificial Intelligence",
        "status": "using"
      }
    ]
  }
}

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