Generative AI (GenAI) is more than hype: it’s reshaping the way that businesses operate. Its capabilities offer endless possibilities for organizations; however, understanding how to tap into its full advantage can be challenging. We can help.
Go beyond AI-driven content, images and synthetic data and leverage the transformative power of GenAI to drive intelligent advantage by creating new products, services and business models.
AI uses with real-world successes
- Increased per-user revenue for an online retailer by 24% by surfacing customer patterns to personalize customer experiences
- Increased revenue for a property rental company by 13% with a generated dynamic pricing system
- Accelerated product development for a consumer goods company by augmenting R&D experts with GenAI to recommend new recipes
- Exploring GenAI-enabled processes for a life sciences firm, including creating compound libraries, predictive affinity models, assisted drug-like properties optimization and more
- Expanding a life sciences clinical data platform to use powerful natural language search, summaries of articles and studies, and interfaces to inventory data via lab management systems
- Augmented strategy exploration for an international manufacturer, enhancing their sustainability approach and reducing emissions by 13%
- Increased coding speed for an online exchange by using GitHub Copilot coding assistant, paired with advisory guardrails
- Automated operations decisions, cutting an airport’s flight delays by 61%
- Increased sales transactions by 4X by enabling a non-technical person to quickly create critical data dashboards through custom prompts
- Harnessed GenAI for creative and business scenario exploration, bringing strategic client conversations to life fast
Keys to continued GenAI success
Create a GenAI plan that closely links strategy to execution to outcome to enable you to adapt and deliver value quickly, then evolve over time. Quick wins are vital to proving out new capabilities, but an overemphasis on short-term gains can block long-term strategic value.
Assess your needs and investments for business value, cost, technical talent and proprietary data. There are multiple approaches to implementing GenAI, each with different trade-offs and these need to be assessed. Use both leading and lagging measures to adapt rapidly.
GenAI is a complex technology, so it is important to have the right talent in place to manage and deploy models. Data scientists, engineers, and product managers who are skilled in generative AI are needed. Leverage partners with experience enabling strategic business processes through technology.
Make sure AI extends your people’s bandwidth and unique skills so that you are accelerating the business’s capacity to grow, innovate and excel. Combine technology and change management in your plans to enable the whole organization.
Ensuring that business and technical stakeholders are aligned on outcomes, measures, and ongoing status is crucial to maintaining organizational momentum over time. Use practices like showcases and putting the software in the hands of users to quickly incorporate valuable feedback.
Build responsible governance to protect your stakeholders, minimize GenAI quality issues, manage cost and intellectual property concerns, and prepare for forthcoming regulation.
Our services include
Drive operational efficiency, great customer experiences and sustainable innovation through business and people-centric AI and machine learning strategies. Build or revisit your AI strategy to take advantage of recent advances in natural language processing (NLP), choose the most valuable business opportunities for AI use, address talent gaps, establish meaningful AI governance and ensure quality training data.
Integrate generative AI, reinforcement learning and classic AI techniques into all you create and do across the enterprise, from personalized customer experiences and dynamic pricing to augmented product design and rich strategic planning and scenario simulation. Identify and implement AI opportunities using human-centric AI-based approaches that outperform machine-centric approaches with fewer computing resources and data.
Place artificial intelligence at the core of your software development lifecycle (SDLC) to enhance functionality, automation and decision making. Train machine learning models, implement natural language processing algorithms, or use computer vision systems to enable intelligent features and improve user experiences.
Establish responsible governance to safeguard the interests of your stakeholders, mitigate the risk of AI inaccuracies, uphold ethical practices, safeguard intellectual property rights, and proactively address regulatory obligations.
Modernize your data platform with AI to automate processes, gain faster insights, and drive continuous improvement. Deploy machine learning models to production faster through MLOps excellence. Build and train GenAI models fast and efficiently. Adapt the principles, practices and tools from continuous delivery to implement MLOps and LLMOps end-to-end processes, enabling increased automation, built-in quality, smaller, more frequent deployments, and repeatable, auditable processes.
