20 Future Jobs AI May Create

Opportunities that artificial intelligence may bring

Posted Mar 04, 2019

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Automation is trending due to advances in artificial intelligence (AI), availability of big data sets, the rise of cloud computing, and decreasing computing costs. By 2025, AI automation will replace 16% of US jobs with an offset of 9% new jobs created, according to Forrester’s June 2016 report. The new jobs that AI will create will fall mostly in the domain of data science, content curation, and automation management.

The boom in artificial intelligence will create a number of new occupations that currently do not exist today. Here are twenty potential new jobs that AI automation may create in the future.

AI Strategist

  • Skills/Background needed: Analytics, communication, management
  • Responsible for creating the overall cross-functional, company-wide plan on where AI will be deployed, how success will be managed, resources required, when it will be rolled-out, and how will it be achieved
  • Interact with internal company stakeholders, outside consulting resources and vendors to produce a cohesive global plan

AI Algorithm Ethicist

  • Skills/Background needed: Philosophy/ethics degree, and/or law degree
  • Work on the strategy, design, and architecture of computer algorithms decisions
  • Responsible for identifying areas where ethics impacts results
  • Create what-if scenario analysis, and an associated action-plan
  • Produce white-papers on AI ethical direction working with legal

AI Globalization Strategy Manager

  • Skills/Background needed: Communication, people-skills
  • Work with the AI Strategist to manage the strategy and deployment of AI in remote and international offices
  • Determine which business functions use AI in the remote and regional offices
  • Manage the localization of data labels for global offices
  • Identify sources for international data sets working with the AI Data Sourcing Manager
  • Determine what can be leveraged from AI implementation in headquarters for other locations

AI Implementation Strategy Manager

  • Skills/Background needed: Communication, analytics
  • Identify and evaluate the best-in-class solutions for AI implementation
  • Cloud hosted, hybrid IT, or completely in-house
  • Use pre-packaged, or home-grown?
  • Work with AI Data Sourcing Manager on data input stream strategy
  • Work with business units for requisite data output reporting and timing

AI Training Manager

  • Skills/Background needed: Communication, people-skills
  •  In charge of managing the ongoing knowledge exchange between AI system and personnel in organizational units
  • Works with internal AI staff and external partners  to create a training schedule and curriculum

AI Lexicon Manager

  • Skills/Background needed: Linguistics, communication
  • Working with the business units, identify data labels and terminology that may cause issues with the algorithms (e.g. idioms, slang terms, etc.)
  • Create and manage the company lexicon of terms for AI
  • Work with the remote and international office on a global roll-up of terms to use

AI Data Traffic Manager

  • Skills/Background needed: Project management, time management, workflow management
  • Manage the smooth flow of data input and output
  •  Create workflows and scheduling of data flows, both in-house and from outside the company

Deep Learning Backpropagation Manager

  • Skills/Background needed: Math, statistics
  • Manage the margin of error in backpropagation
  • Produce timely reporting on data output precision
  • Work with the AI Data Algorithm Manager to continuously fine-tune the margin of error

AI Business Analyst

  • Skills/Background needed: Analytics, communication
  • Compare the performance of business processes/units that use AI
  • Develop and maintain performance metrics to measure how much AI moves the needle in profitability and other metrics (customer satisfaction, employee satisfaction, etc.)
  • Tie figures with company-wide business intelligence system
  • Provide inputs that can be used as a data point of reference in monthly, quarterly and yearly performance reporting

AI Data Algorithm Manager

  • Skills/Background needed: Mathematics, statistics, computer science
  • Evaluate and compare different types of algorithms to use in AI systems, and the impact on quality vs. speed

AI Security Manager

  • Skills/Background needed: Computer science
  • Determine areas of vulnerability in the AI system
  • Create and manage a plan to mitigate or prevent AI security issues

AI Computer Vision Specialist

  • Skills/Background needed: Computer science
  • Prevent mislabeling and computer algorithm being “fooled” by data input
  • Create and maintain databases of visual errors working closely with the AI development team and AI Data Integrity Manager

Deep Learning Training Manager

  • Skills/Background needed: Computer science, data science
  • Work cross-functionally with business units to decide, implement and manage the optimal strategy for training the AI algorithm (e.g. Supervised training, Semi-supervised training, and/or Unsupervised training)
  • Manage the training of the algorithm and provide regular management reporting on performance and issues

AI Transition Specialist

  • Skills/Background needed: Human resources, communication
  • Work on retaining, retraining, and repositioning workers displaced by automation into other areas either within the company

AI Performance Analyst

  • Skills/Background needed: Analytics, communication
  • Define the metrics of success with business units and stakeholders
  • Measure the satisfaction both internal (business unit) and external (customers, partners, vendors, suppliers, etc.)

AI Data Integrity Manager

  • Skills/Background needed: Communication, data science
  • Encourage data diversity and relevance
  • Monitor and assess data quality
  • Strive to minimize data biases
  • Work closely with AI Algorithm Ethicist and AI Data Algorithm Manager

AI Algorithm Behavioral Manager

  • Skills/Background needed: Management information systems, communication
  • Define the range of desired AI outcomes and create a plan on how various organizational groups/responsibilities need to respond as needed
  • Work closely with the AI Security Manager and AI development team to create a disaster recovery plan

AI Data Sourcing Manager

  • Skills/Background needed: Communication
  • Locate, negotiate big data sources needed for the AI algorithms working with the AI development team
  • Evaluate areas where in-house data can be used working with the CIO and information systems department
  • Manage the data sourcing alliances and partnerships

AI Deep Learning Documentation Manager

  • Skills/Background needed: Communication, data science
  • In charge of managing the data labels for training computer algorithms working closely with the AI product development team
  • Create ongoing databases of data labels to use, and not-to-use

AI Emerging Markets Manager

  • Skills/Background needed: Business analytics
  •  Identify and scope future areas where AI may be deployed in the organization and geographies
  • Work with AI Strategy Manager to provide input on future business opportunities and AI rollouts

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