Dec, 27, 2022.
The Need for Artificial Intelligence
As with every Industrial Revolution that has altered the course of humanity’s history, Industry 4.0 is currently rewriting the global landscape on a second-by-second basis. As we know it today, life has become inextricable from the defining technologies of the 4th Industrial Revolution, most notably Artificial Intelligence.
Artificial intelligence (AI) is rapidly transforming the productivity and GDP of the global economy. AI could contribute up to $15.7 trillion to the global economy by 2030, more than the current output of China and India combined. AI is driving this economic growth by making prediction and automation cheap, reducing cost, uncertainties, and inefficiencies in many processes, and enhancing the quality of services with hyper-personalization at scale. AI is doing this in every imaginable sector and facet of today’s world.
The Need for a Winning AI Strategy
The success of your organization in today’s fiercely competitive market rests on how well it can outperform others in the areas of hyperpersonalization, quality service, and cost savings.
The challenge is not that executives are unaware of AI and its potential benefits but rather that they have no idea how to craft transformative or winning AI strategies. This leads to a cycle of failed deployments and cash burn that further weakens the competitive position of the organization.
The goal of this article is to deconstruct the technicality of AI implementation by showing the building blocks upon which successful AI implementation rests.
Building a Winning AI Strategy
“Everyone has a plan until they get punched in the mouth.” – Mike Tyson.
This quote is as true in boxing as it is in the corporate world. A single setback can knock off strategies. This makes it essential to build an expansive and in-depth system as far as AI adoption is concerned.
At Stallion AI, we build winning AI strategies by utilizing our proprietary AI Readiness Assessment & Strategy (AIRAS) framework.
AIRAS is an industry-focused comprehensive and practical methodology that measures the ability of an organization to successfully develop, implement and use AI and machine learning to drive business value. It evaluates the capacity of an organization to sustain a level of excellence in cost-effective and transformative machine learning development, deployment, and data-driven decision-making over multiple projects.
The AIRAS Methodology
Behind every successful AI strategy is a well-grounded foundation in machine learning. Building a rock-solid ML platform requires being in control of data across three stages – acquisition, analysis, and integration. As a result, Stallion AI’s AIRAs methodology drills into an organization’s capacity to support these stages through its policies & processes, infrastructure, and skills’ level.
By exploring an organization’s Data-Analysis-Integration scores, the methodology probes into the strength of the organization’s ML pipeline while the Policies-Infrastructure-Skills scores reveal where finetuning is required to improve the pipeline. For example, understanding what combination of training courses versus hardware and software upgrades or data purchases might be most impactful.
In peeling back the layers of an organization’s AI strategy, the AIRAS framework narrows in on 12 key areas of examination:
Strategy – To what extent can an organization’s leaders define a vision and its KPIs?
AI Use Cases – What are the challenges facing the organization’s proposed near and long-term AI use cases?
Data – How much of a role does data play in guiding an organization’s business operations and how is the data collected and analyzed?
Culture – Has the organization created a culture that supports innovation?
Ethics – How committed is the organization to ethical assessment, design and training?
People & Skills – At what technical skill level is the organization’s human talent pool and how passionate is the organization about raising these standards?
Data Strategy & Acquisition – The organization’s data gathering and storage capacity.
Data Understanding – How adept is the organization’s data science team at unraveling data?
Data Science & Infrastructure – Does the organization possess the requisite hardware and software infrastructure?
AI/ML Project Practice – What level of upper management support do AI/ML projects receive?
ML & Data Science Skills & Practice – How capable is the data science team at building, testing and validating ML-trained projects?
ML Deployment and Integration – How capable is the data science team at deploying trained ML models and integrating them into the organization’s business operations?
AIRAS in Practice
The AIRAS framework is an ever-evolving methodology that has yielded fruit since its conception. Stallion AI has collaborated with several public and private organizations to conduct its AIRAS program which includes assessing AI maturity levels, capacity building for business and technical leaders in AI and data science within their own domains, and constructing an AI roadmap of feasible and high-impact projects.
Partners that have successfully adapted Stallion’s AIRAS program include elite organizations such as the Dubai Police, UAE’s Ministry of Infrastructure & Development, Dubai Financial Market, Jordan’s Ministry of Digital Economy & Entrepreneurship, Umniah Telecommunications, etc.
Stallion AI has recently conducted a National AIRAS Program for the Jordanian government. As of December 2022, 18 Ministries have been evaluated using the AIRAS framework with the following key statistics:
· Stallion AI secured the participation of over 3,090 government leaders and professionals.
· The company raised AI awareness in the government sector workforce by 26%.
· The AIRAS methodology yielded more than 15 transformative AI projects in a 5-year roadmap for each Ministry/sector.
AI adoption is a journey rather than a destination requiring that every step be well thought-out to avoid missteps. The best time to begin this journey was yesterday. With Stallion AI’s AIRAS methodology, organizations have what it takes to soar to the peak of AI transformation.
If you are planning to transform your organization with AI and data, do not hesitate to consult with our AIRAS team at email@example.com
Tue, Dec, 2022 15:08
Thanks for explaining difficult concept in this fantastic and insightful article. Appreciate it.