Create Language Consensus and Consistency. 

AI is more than coding and programming. It requires consensus on taxonomy and terminology, which can vary widely from one product and stakeholder group to another. New standards, including defining metadata and data dictionaries are necessary. Getting alignment across functional areas on those standards is the most challenging part. 

These are issues that put your people at the center of change. The implementation and application of AI technology is rooted in a very human element: language. The process requires multiple departments and stakeholders to agree on a set of standards. That may not be easy when, historically, there’s been little need for consistency from group to group. Companies often underestimate the amount of time it takes to align key stakeholders on language alone. 

Change management, in addition to a set of taxonomy and terminology standards, is needed to create consensus.

Develop an integrated approach that builds ownership. 

AI requires buy-in from an array of extremely specialized professionals across disciplines. Integrated planning and clear ownership create the level of accountability you need for AI to succeed. This takes strong sponsorship, particularly at the executive leadership level.

Here are a few activities you can do to build an integrated approach and ownership:

  • Business problem and use case analysis
  • Gap assessment and business case development 
  • Cross-functional initiative design and planning
  • Business requirements development
  • Data standards, governance and information architecture
  • Technology strategy and vendor selection
  • Implementation planning, execution & change management

We find that leaders are best able to see the need for executive focus and accountability when they look at AI through the lens of business objectives. It takes input and inclusion from the bottom-up, including two-way communications with diverse stakeholder groups. What’s in it for them?

Determining The Right Technology And Partners. 

We recognize that AI is one of many advanced technologies. Machine learning, natural language processing (NPL), natural language generation (NLG), robotic process automation (RPA), structured content management, and auto-content generation are all valuable tools that can create speed and efficiency for enabling products’ go-to-market. Many of these require similar data standards, process definition and internal alignment. Determining which technology is best suited for the use cases in scope is a critical step in the journey – AI is not necessarily right for all situations. 

The AI vendor landscape in life sciences is rapidly evolving. Vendors and products cover many categories, including process automation, structured content management, master data management and governance, and more. The right vendor will save you time, money and headaches while optimizing business value. We help life sciences companies navigate this complicated selection process and build strong partnerships with vendors that are best for them.

Where Do You Begin?

Build a time-boxed proof of concept.  

When clients aren’t sure how to start - or if it’s even worth the investment - we suggest trying a time-boxed proof of concept. It’s an effective way to show how it could work and what’s achievable to a variety of stakeholders. We can quickly design and showcase new ways of working or applications of new technology. Tackling a specific problem on a very small scale lets you learn from that experience, then refine and scale with an iterative approach that will increase the success of any future plans. 

It's “when,” not “if.” Grow your AI maturity level over time. 

Every organization has its own AI needs and objectives. While it can be tempting to keep up with the trendiest technology, it’s far more important to understand what AI can do for you and your goals. You’ll also need the data readiness, infrastructure, governance and organizational strategy that will enable AI to meet your goals. AI is an evolution in maturity—understand where you are in the journey and take steps forward.

It’s still early days—with years of discovery and amazing opportunities ahead. What better time to master the fundamentals?


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