Archive for September, 2018


Research: Get your Company Ready for AI

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In a world of fleeting tweets and memes, it’s important to ground your business based on in-depth research. Kaleido’s latest 50-page report on AI Readiness, get your company on the right track as they adopt automation. We offer both a sample at no-cost, and ability to purchase the entire 50-page report.

I’ve been interviewing many companies on how they’ve been rolling out AI for their customer-facing engagements as well as for customer care use cases. One thing is very clear, they’re experimenting, and in most cases, they don’t have the full support of the rest of the organization.

My talented business partner Jessica Groopman, has published an in depth 50-page report which gives unseen insights, pragmatic recommendations based off interviews and research on how companies need to be prepared for AI. Surprisingly, much of the readiness isn’t just about getting technology and data cleansed –there’s many cultural, impacts, including preparing employees and even setting up a clear code of ethics.

Don’t just dump your company’s data and brand into an AI engagement without having a larger program that reflects five different areas:

  1. Strategy: AI-driven transformation begins with ground-up problem-solving, but must be supported by a foundation of governance and aligned with business objectives and enterprise data strategy. While approaches and metrics vary by organizational maturity, customer experience is always true north.
  2. People: Preparing people for AI is as important as preparing data, and it is essential for businesses to prioritize human factors over technological capabilities. Instill the “AI Mindset” across myriad stakeholder groups; foster lockstep coordination between technical and product, and address AI’s limitations and cultural stigma head-on.
  3. Data: Data preparedness is not a linear destination. AI data readiness requires organizations address their broader data strategy and orchestrate data pipelines and resources for ongoing enterprise learning and evolution.
  4. Infrastructure: Decision-making around the technical architecture and integrations required to deploy AI must align with core product strategy, balance reliability with flexibility, and account for rapidly evolving AI software, hardware, and firmware.
  5. Ethics: The mass automation of big data and AI call for a new business competency: a formalized approach to organizational resources, bias assessment, transparency, and ethical preparedness.

Get the report, and get your company ready for AI.