Key Recommendations Earn employee buy-in with augmentation. The most immediate way to positively impact your business results is practitioner augmentation, automating repetitive tasks. However, this approach should be developed in tandem with employees, not dictated to them. Adopting genAI capabilities that are already part of the tools you use — like creative suites — is one part of the puzzle. The other is working directly with employees to see where they want to leverage genAI. This collaborative approach will not only help time to value but increase your organizational familiarity with genAI tools and improve your own access to genAI-attuned talent. Fund knowledge and data hygiene initiatives. The first step to effectively leverage genAI is foundational data management, which half of NA M&E decision-makers say they lack. While M&E firms have an overabundance of data, metadata normalization and common schema efforts are lacking. Having people who understand and catalog it is a first step in remediation. Establishing the position of chief data officer and ensuring their office has funding for data scientists and analysts who can index, clean, and identify inconsistencies will be needed to embed into genAI implementation teams. While there are automation tools that will help with these activities, data experts will be needed to provide architectural expertise. Prioritize trusted partners and premade solutions. While many adopters are still working through fine-tuning their own models, poor performance and skills shortages limit business impact. As organizations orient to business value, partner selection should be the next step. Focus partner selection on two fronts: 1) those who can help with legacy systems modernization and data efforts and 2) those who can bring premade vertical specific solutions to bear across generative modalities. Prioritize MSPs and strategic tech providers who can supplement your skills, abstract away the complexity of managing a genAI stack, and assure your ownership over your data. Adopt a federated strategy. Today, most M&E firms follow a centralized model of genAI management: one team in charge of everything, from adoption to policy to development. While centrality allows for effective governance, it also serves as a rate limiter. While NA M&E firms have been quicker to embrace federated teams, central control remains the primary way firms organize around genAI. As modalities and embedded tooling proliferate, this model must change to better incorporate other lines of business. Adopting a federated model — with a central team reviewing for privacy, data security, policy adherence, training, and supporting development/adoption efforts at the organization and team level — allows for faster integration into daily workflows. 15 © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. © FORRESTER RESEARCH, INC. ALL RIGHTS RESERVED. 14
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