Artificial Intelligence and Machine Learning
We help organizations choose the right Artificial Intelligence projects and the right approach that combine to deliver transformational business outcomes
Organizations are facing an unprecedented challenge. Surviving and overcoming competition requires transformation of all aspects of the enterprise with artificial intelligence (AI) and machine learning (ML). Although the transformation must be accomplished on a speedy timeline, cultural and communication differences
between business owners and data scientists can impeded progress. Bridging the differences, surfacing domain and AI knowledge, and joining together the AI artisans and business owners builds a new data-facing culture and unlocks the potential that AI and ML can deliver for the transformed organization.
How We Help Clients
Assess Execution Readiness
We help organizations assess their readiness to adopt, adapt, and leverage AI tools to achieve lasting and transformational business outcomes. We assess across many aspects that are essential ingredients for success including technical, cultural, and leadership readiness elements.
Upskill Execution Capabilities
Blackstone+Cullen works with executive leadership, line staff, and business owners to de-mystify AI and ML and to provide coaching and resources needed to instill knowledge, confidence, and ability to execute on AI initiatives. We help rollout tools, capabilities, and performance measures to reinforce the organization’s ability to start, steer, and finish successful AI programs.
Lead AI and ML Implementation
We lead machine learning projects with and for our customers. We combine on-site engagement with remote support to work with data scientists, analysts, business owners, and executive sponsors. We lead the way in use case selection and problem definition, exploratory data analysis (EDA), modeling, migration to production, and post-production monitoring.
What We Do
Strategy Development
Building a credible strategy and recognizing the strongest, most valuable, and most practical use cases for AI implementation. Defining technical, process, and cultural challenges to transformational success and reliable approaches to overcoming each.
Capability Building and Coaching
Upskill training for executives, business owners, IT staff, and developers. Conducting exploratory sessions to uncover high-value use cases not previously recognized.
Machine Learning and Application Implementation
Use case design, exploratory data analysis (EDA), model building, development, training, and testing. Support for your IT team in migrating the application to production. Post-production monitoring and tuning.
AI and ML DevOps Development
Organizing and staffing an AI DevOps capability, the function that is often the missing ingredient in propelling AI projects forward to production success and business value achievement.
Strategy Roll Out
Building and executing on strategy for AI implementation to transform the business.
Program Management
Defining and managing a program plan and PMO to guide transformation.
Our Approach
We lead our clients to success from well-considered strategy through skillful implementation
We bring people and knowledge together to promote a vision of AI and ML as practical and powerful tools needed to lift all parts of the organization to full competitiveness, not as trendy management tools that may have little impact. We choose strategic projects with the greatest and most transformational value to the enterprise.
Strategic Prioritization
Strategic prioritization yields outstanding return to effort by finding use cases that offer great value to the business, that solve a real business problem, and that are technically feasible.
Upskilling for Cultural Change
Leaving behind large parts of the organization when embarking on digital transformation ensures program failure and negative attitudes. Upskilling on a widespread basis for AI and ML awareness and hands-on skills is quick and inexpensive. Upskilling is also rewarding for team members and effective at surfacing unrecognized but valuable use cases for AI.
Instilling a DevOps Vision
The first AI project, no matter how basic, should establish a process pipeline connecting a use case to production through the DevOps team. The pipeline will be used repeatedly to migrate updated ML models that are embedded in production code, as well as for moving new projects to production. The pipeline and DevOps engagement are critical for continued success.
Avoiding Pilots
Pilots are easy to complete but seldom have a lasting business value. Pilots often fail to engage IT or DevOps until late in the project, often lack committed executive sponsorship, and are often chosen by someone other than an enthusiastic business owner with a real problem to solve.
Avoiding Moonshots
AI programs of massive size have a high failure rate. These should be decomposed into smaller projects that typically have a much greater success rate.
Sectors We Serve
- Chemicals, Metals, and Mining
- Distribution
- Electric Power & Natural Gas
- Engineering, Construction, Building Materials
- Financial Services
- Manufacturing
- Oil & Gas
- Pharmaceuticals & Medical Products
- Public Sector
- Technology, Media & Telecommunications
- Travel & Hospitality
Impact Stories
Increase Rental Fleet Utilization Using an Artificial Intelligence Engine
Global Lead Allocation Across All Business Units
Increase Sales Quota by Identifying Next Most Likely Purchase
Complex Problem Solving
Our People
Understand how our team can help your organization with AI and Machine Learning.
Elizabeth Hancock
Greg Ashworth
Chuck Huels
