Google Cloud Put AI to work across your business
We help professionals cut manual effort and integrate systems. See exactly how our teams use artificial intelligence to complete tasks in minutes instead of months. Schedule a free workshop to identify high-impact AI use cases across your organization.
Explore AI business use cases and tools for every role.
Filter by tool to see how Insight’s experts apply AI across core roles — from sales and dev to FinOps and legal — to eliminate manual effort and deliver ROI.
SVP Sales
The challenge:
Approving complex Statements of Work (SOWs) takes immense manual effort, and navigating an inbox of 7,500+ messages causes critical deal delays.
The AI solution:
Uses an AI inbox to triage tasks, and deploys deep research agents to scrape internal and external data on clients. Instantly generates a Rough Order of Magnitude (ROM) and drafts SOWs — complete with project milestones and server migration costs.
The impact:
Cut the front-end creation of an SOW from an eight-hour manual undertaking to a matter of minutes.
"Be bold, be brave, and break stuff. You don’t need an engineering degree to push boundaries — intentionally test the limits to discover what the tool can actually accomplish for your specific workflow."
Senior Account Executive
The challenge:
Waiting up to five weeks for engineering resources to draft cloud consumption estimates and ROI models for executive client pitches.
The AI solution:
Feeds historical SOWs and complex financial data into AI to build aggressive consumption estimates for funding. Manages over 100 dedicated AI notebooks to turn raw meeting transcripts into highly technical service recommendation emails and ROI payback graphs.
The impact:
Cut the workflow for technical consumption estimates down by weeks, and reduced the time spent drafting comprehensive client emails from 30 minutes to just four minutes.
"Always ask for explicit permission before recording a meeting, and make call transcripts your best friend. Give yourself weekly or monthly briefings on your own data so you are more prepared and credible in all of your meetings."
Associate CTO
The challenge:
Researching, designing, and coding complex cloud architectures
The AI solution:
Orchestrates multi-agent workflows — spinning up one AI agent to research workspace data and another to research Kubernetes simultaneously. Instructs the AI to design a cloud architecture, draft the documentation, and build custom chatbots.
The impact:
Built and deployed 10 internal applications and chatbots in 10 weeks, replacing a manual process that would have taken months to complete.
"Be critical of AI. If it takes you longer to write the prompt to create a calendar invite than it does to just click the calendar and make the event yourself, skip the AI. Question the utility of every single interaction."
FinOps Analyst
The challenge:
Manually writing complex BigQuery SQL scripts to extract highly specific data subsets from multi-terabyte cloud billing datasets.
The AI solution:
Feeds client transcripts into AI to architect dashboard layouts, and then asks it to write the exact SQL code to introduce complex parameters like contract discount percentages.
The impact:
Cut the time required to write, tinker, and test complex SQL queries from 45 minutes down to 15 minutes.
"Never blindly trust the output. Treat AI strictly as a quick-start engine, and always double-check the logic and column names to prevent compounding errors in your database."
Principal Developer
The challenge:
Resolving deeply technical software bugs and navigating thousands of lines of messy, unstructured codebase logs.
The AI solution:
Uses multi-agent workflows where one AI writes code and another acts as a gatekeeper to debate the design until they reach a consensus.
The impact:
Fixed a critical software bug in a single day that had previously stumped the team for three months, achieving a 2x to 20x speed boost on routine development tasks.
"Stop starting from scratch. Build a detailed user profile and force the AI to load your value system and historical preferences before beginning any task. The AI fails when it doesn't know you."
Legal Counsel
The challenge:
Redlining 60-page vendor agreements and manually searching historical contracts to interpret complex, ambiguous language.
The AI solution:
Uploads legal playbooks and instructs AI to take the first pass at redlining new agreements strictly based on those rules, flagging clauses that stray from standard positions.
The impact:
Reclaims up to half a day’s worth of work previously spent on manual redlining, locating specific contract clauses in seconds instead of a 45-minute search.
"For seasoned veterans, the hardest part is detaching your mind from the way you've always done things. You have to get comfortable being uncomfortable with new processes if you want to speed up your reviews."
Talent Development Professional
The challenge:
Creating comprehensive, multimedia training materials and asynchronous learning tracks to upskill technical teammates.
The AI solution:
Uses AI to outline training decks, script roleplay scenarios, and instantly generate multimedia video examples.
The impact:
Designed an entire workshop in just half a day — eliminating a two-to-three week wait time previously required for an instructional designer.
"If you don't know what a good final product looks like, you will get a junk out situation. Only use AI for tasks where your expertise allows you to spot hallucinations and quickly validate the quality."
Brand Marketer
The challenge:
Developing foundational brand messaging for a company undergoing a complete rebrand, and getting up to speed on unfamiliar technologies.
The AI solution:
Ingests weeks of strategy meetings to gain instant context, building cohesive messaging guides that let clients self-serve their content creation.
The impact:
Enhanced the quality and cohesiveness of the output, building narratives in record time without relying on subject matter experts.
"Use it as a tool, but never put your own brain on autopilot. Refuse to let it generate slop — always use your human discernment to challenge subjective suggestions rather than accepting them as gospel."
Public Sector Sales Lead
The challenge:
Parsing 40-document Requests for Proposals (RFPs) and researching obscure government agency contacts to formulate viable talk tracks.
The AI solution:
Investigates government contacts to build tailored outreach strategies, and searches past contracts to find specific concessions made years ago.
The impact:
Successfully located a highly specific contract concession from three years ago — a “needle in a haystack” that unblocked a live negotiation.
"Stop typing out perfect prompts. Plug in an external mic and simply monologue an unstructured problem out loud. Use it as an online mentor to bounce ideas off of and find a missing nugget of insight."
Business Operations Analyst
The challenge:
Allowing non-technical users to access the data warehouse securely, and matching 9,000 messy, legacy customer records across disparate systems.
The AI solution:
Built a natural language conversational agent on top of the data warehouse, allowing sellers to pull complex IDs right in their chat window without needing deep system access.
The impact:
Successfully mapped an entire legacy customer base using public market data — a massive data alignment project the organization had tried and failed to accomplish manually for years.
"Success requires explicit boundaries. Be highly intentional about limiting what the AI can access and restricting what it thinks it can answer, rather than giving it free rein over your entire data warehouse."
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