IDC's Artificial Intelligence Strategies program assesses the state of the enterprise artificial intelligence (AI) journey, provides guidance on building new capabilities, and prioritizes investment options. The research puts AI in the context of business transformation and addresses topics of growing importance to C-level executives, key decision makers, and influencers. These topics include build versus buy, AI data readiness, embedded AI, pre-built AI applications, hybrid and multicloud architecture impact on AI build and deployment pricing models, trustworthy AI, , augmented AI, and machine learning (ML) operations. This IDC research service also addresses the needs of AI and ML technology vendors that are incorporating AI and ML into their next-generation offerings. The service helps vendors that face decisions about how to convey their value proposition in a crowded market, how to differentiate their offerings, and how to keep abreast of the latest demand trends.
Artificial Intelligence Strategies
Markets and Subjects Analyzed
- Overall maturity of artificial intelligence transformation in the industry
- Insight about AI governance, top and emerging AI use cases, customer implementations best practices, and pricing and packaging trends
- Machine learning operations — MLOps
- AI Applications across industries and business processes: Conversational AI, Computer Vision, Intelligent Automation, Recommendation Engines, Predictions, Decisioning, and ADAS
- Trustworthy AI — fairness, explainability, robustness, lineage, and transparency
- Impact of edge, hybrid cloud, and multicloud architectures on AI lifecycle
- Democratization and operationalization of data for AI
- AI marketplace
- AI as a service
- AI ecosystems
- Enterprise AI Journey — IDC MaturityScape
- Global AI Adoption Trends and Strategies — End-User Surveys
- AI Adoption Best Practices — Buyer Case Studies and IDC PeerScapes
- Artificial Intelligence, Machine Learning, and Deep Learning Market Analyses and Predictions — IDC FutureScape and MAP
- AI Software — Applications Market Trends, Forecasts, and Vendor Market Shares
- Model Validation, Monitoring, Management, and Deployment — Tools and Technologies
- Fairness, Explainability, Robustness, and Transparency — Tools and Technologies
- Data for AI Including Synthetic Data Generation
- Ecosystem Partnering Strategies — Technology and GTM
- Machine Learning and Deep Learning Tools and Technologies Advancements and Futures — Federated Learning, Neuro-Symbolic AI, NLP Fine-Tuning
In addition to the insight provided in this service, IDC may conduct research on specific topics or emerging market segments via research offerings that require additional IDC funding and client investment.
Key Questions Answered
- What constitutes superior AI transformation maturity relative to peers?
- What are the AI software trends and advancements to accelerate AI adoption?
- What are the leading ML and deep learning uses for enterprises?
- What are the new rules for a build versus buy decision for AI?
- What are AI applications, and how are they accelerating business transformation?
- What is needed to realize AI and ML at scale?
- What is augmented AI, and what are the leading drivers and trends?
- What are the pricing dynamics for monetizing AI capabilities?
- What are the trends and growth rates for on-premises, cloud services, or edge for AI training and inferencing?
- What are the advancements in tools and technolgoies to support enterprise trust, security, and explainability needs for AI?
Accenture plc, Adobe Systems Inc., Amazon.com Inc., Capgemini Services SAS, DataRobot, Inc., Databricks Inc., Dataiku SAS, Google LLC, Hewlett Packard Enterprise, IBM, IPsoft Incorporated, Infor, Inc., Infosys Limited, Intel Corporation, Microsoft Corporation, MixMode Inc., NetApp, Inc., OpenText Corporation, Oracle Corporation, SAP SE, SAS Institute Inc., Salesforce.com, Inc., ServiceNow, Inc., Tableau Software, Inc., The MathWorks Inc., Workday, Inc.