Value and strategy
- Value realization
- Strategy and use-case sprawl
89%
of AI agent pilots fail to reach production.
AI researches, drafts, and runs the workflow. You own the decision, and you bring the creativity, taste, and judgement. That is HI + AI, and it is how bostoncyberx helps your business achieve more intelligent operations.
89%
of AI agent pilots fail to reach production.
21%
have a mature governance model for agentic AI.
29%
feel ready to secure the agentic AI they deploy.
78%
struggle to integrate AI with existing systems.
52%
worried about AI's impact on their job.
48%
uneasy telling a manager they used AI.
77%
say AI tools added to their workload.
Perspective informed by NIST AI RMF / GenAI Profile, NIST Cyber AI Profile draft, OWASP Agentic Top 10, MITRE ATLAS, and NIST CSF 2.0.
Stat sources: Gartner (2026), Deloitte (2026), Cisco (2026), Zapier (2025), Pew Research Center, Slack Workforce Index, Upwork Research Institute.
The pattern is familiar: employees are already pasting work into ChatGPT, a Copilot pilot stalled, and the board wants an AI plan nobody owns.
Most organizations have AI activity. Few can show it paid.
of organizations are AI high performers, attributing more than 5% of EBIT to AI and reporting significant value.
Source: McKinsey, The State of AI in 2025.
The rest get stuck in a familiar loop: a pilot that never leaves the lab, siloed trials that never sit on one strategy and roadmap, or a mandate to "use AI" or "tokenmax" with no metric that says which bets worked.
bostoncyberx helps you run the program as one sequence. Our methodology helps identify the use cases that pay, write the rules, put owners and measures on each bet, then roll out and train against those numbers.
We score candidate use cases by return and risk, then sequence the two or three worth doing first into a roadmap with owners and dates.
Acceptable use policy, vendor review, data boundaries, and oversight rules aligned to NIST AI RMF, written so auditors and insurers can read them.
Guardrails first: permission cleanup, data controls, and logging, then a pilot with a defined group and defined success metrics.
Role-based sessions on what the tools do well, what they get wrong, and what data never leaves the building.
A baseline before rollout, monthly reporting after. If a use case is not paying, we say so and redirect the budget.
Every recommendation is vetted for data exposure and vendor risk, because the firm defending your environment is the one advising on AI.
The companies that scale AI successfully are the ones that governed it early.
Without governance, legal blocks deployments, IT blocks integrations, and employees route around both with personal accounts. With clear rules, deployments move.
Ongoing ownership of strategy, governance, vendor decisions, rollout, and training, with deliverables in writing. Typical range is $5K to $30K per month.
Defined outcomes at defined prices: a governance build, a Copilot deployment, a roadmap, or a vendor review. No hourly meters.
Ranges reflect companies with 25 to 1,000 employees. Your scope sets your number, in writing before you commit.
Rarely. Most companies get more value faster from configuring commercial tools with the right guardrails and data boundaries. We recommend a custom build only when off-the-shelf cannot meet the requirement and the return justifies the cost.
We stay through deployment: the team that writes the strategy configures the tools, writes the policies, and trains your people. And we are a security firm, so every recommendation is already vetted for data exposure, vendor risk, and compliance.
Most clients have their first governed use case in production within 90 days: policy in force, a sanctioned tool with a pilot group, and a measurement baseline. Larger rollouts run quarterly with metrics reported monthly.
The free readiness assessment scores your AI use, data, and governance in ten minutes. You get a baseline and the three moves that matter most before anyone books a meeting.
Take the free AI Assessment