Scaling AI adoption securely on AWS with GuidePoint Security and DoiT

GuidePoint had already introduced generative AI to parts of the business, but it wanted to make the technology more accessible across roles while maintaining consistent governance. As a remote, regionally structured cybersecurity company, it needed an enterprise environment that could support different levels of AI experience without restricting how teams worked.

GuidePoint also wanted adoption to grow from real business needs rather than a single standardized process. To support users at every level of the AI experience, the company needed one approachable environment with advanced security features.

To keep data inside the AWS environment that the company already operated in, GuidePoint chose Amazon Quick for research, business insights, and automation. Its capabilities gave teams flexibility to explore appropriate AI use cases while operating within GuidePoint’s existing governance requirements. This managed productivity environment can connect enterprise data sources while respecting identities, roles, and permissions. Because AWS provides built-in governance and security controls, the company can enforce governance centrally under the Shared Responsibility Model.

GuidePoint brought in AWS Partner DoiT to assist the rollout. To demonstrate real, measurable impact, the team applied the AWS Business Value Realization framework and defined target outcomes before touching implementation. The goals were a 20–25 percent reduction in research hours and broad adoption, which the team tracked through weekly and monthly active users.

GuidePoint rolled out access carefully, starting with a small pilot group and expanding access in phases. A cross-functional team paired the rollout with live education, online resources, and hands-on workshops, giving employees practical guidance on responsible use, human verification, and evaluating AI-generated output. Superusers in each department served as advocates and trainers, helping colleagues apply the tool to their daily work. This phased approach gave employees time to build skills while GuidePoint maintained the access controls that sensitive data requires. Adoption grew through practical, team-specific use cases shaped by the employees closest to the work.

GuidePoint scaled from a 150-person pilot to 1,500 employees in 6 weeks, and uptake was close to 100 percent. Employees across the business now use it to develop workflows around the work they know best. In Learning and Development, the team automated recurring KPI reporting and turned subject-matter-expert notes into a new-hire course outline during a single meeting, a task previously estimated to take 2 days. Teams compiled a competitive analysis report in 4 hours instead of 2 weeks, turned speaking-session submissions into a searchable catalog in 30 minutes instead of 20 hours, and managed a weekly marketing-operations workflow in 30 minutes instead of 3–4 hours. By automating the most labor-intensive step in a pre-event marketing workflow during one major event week, GuidePoint saved over 60 hours.

In client delivery, practitioners use Amazon Quick to streamline research, organize notes, and analyze tool output so they can spend more time on interpretation and recommendations that require human judgment. “Adoption grew because employees built solutions for problems they actually have,” says Ed Dunnahoe, vice president of innovation at GuidePoint Security. “Amazon Quick has accelerated AI adoption by giving us a governed way to connect AI with our enterprise applications, empowering employees to safely build solutions to the challenges they face every day.”

Based in the United States, DoiT helps customers with AI initiatives and financial operations.