As enterprise and government leaders develop artificial intelligence (AI), data governance, and cloud migration strategies, the need for a unified framework has grown substantially. These strategies naturally overlap, presenting challenges spanning from strategy development through to implementation. High-quality, governed data fuels impactful AI, which is enabled through the proper cloud infrastructure.
All data science, AI, and machine learning (ML) endeavors can be thought of as sets of experiments. Similar to laboratories in the natural sciences, these efforts require the availability of and access to high-quality samples, cutting-edge techniques and equipment, and the space and security of a controlled environment capable of handling the workload. To meet these needs, organizations must align their cloud strategies, data, and AI so that the “science” behind data science can thrive.
Guidehouse brings unique, combined expertise in applied sciences, life sciences, AI, cloud, data governance, IT strategy, and change management. This diverse but tightly coupled set of capabilities positions us to design and build the Ultimate AI Lab, ensuring fertile grounds for ML algorithmic experiments to sprout the most promising models and deliver impactful and reliable predictions. Leveraging these competencies to develop an integrated cloud, data, and AI strategy has a variety of benefits:
Cloud: Creating an agile, data-driven cloud practice facilitates cost-effective, secure, and observable operations. Insights and applications have reduced time-to-market, are more reliable, and can be governed without sacrificing value.
Data: Strategic priorities are bolstered by secure cloud infrastructure. The value of the organization’s data is realized quickly and efficiently by AI and IT operations.
AI: Integrated strategy enables AI teams to develop an Ultimate Lab where data is discoverable and computational resources are scalable and secure.