Strategy

AI Strategy for CEOs: Aligning Tech with Business Goals

Published

Nov 13, 2024

Author

Charles Humble

Associate Editor

Join Phil Winder and Charles Humble in this insightful interview as he delves into the critical components of an enterprise AI strategy, based upon his excellent article on the subject.

Gain actionable insights on aligning AI with your business goals, building robust data infrastructure, and prioritizing projects based on ROI. Learn about MLOps, AI security, and the role of generative AI and reinforcement learning across industries.

Getting Enterprise AI Strategy Right

Published

Sep 13, 2024

Author

Charles Humble

Associate Editor

AI offers considerable benefits across almost every commercial enterprise, from efficiency gains to the potential for brand new products. But it also represents a threat, opening up possibilities for new entrants to disrupt established markets. In business environments, company executives look to produce an ‘AI Strategy’ but can lose sight of their objectives, rather like a politician thinking, “Something needs to be done and this is something, so let’s do this.

Improving Data Science Strategy at Neste

Published

Aug 7, 2020

Author

Dr. Phil Winder

CEO

Winder.AI helped Neste develop their data science strategy to nudge their data scientists to produce more secure, more robust, production ready products. The results of this work were: A unified company-wide data science strategy Simplified product development - “just follow the process” More robust, more secure products Decreased to-market time Our Client Neste is an energy company that focuses on renewables. The efficiency and optimization savings that machine learning, artificial intelligence and data science can provide play a key role in their strategy.

Cloud Native Data Science: Strategy

Published

May 2, 2018

Author

Dr. Phil Winder

CEO

Data Science has become an important part of any business because it provides a competitive advantage. Very early on, Amazon’s data on book purchases allowed them to deliver personalised recommendations whilst customers were browsing their site. Their main competitor in the US at the time was Borders, who mainly operated in physical stores. This physicality prevented them from seamlessly providing customers with personalised recommendations [1]. This example highlights how strategic business decisions and data science are inextricably linked.

The Benefits of Outsourcing Research and Development

Published

Apr 13, 2016

Author

Dr. Phil Winder

CEO

When I think about my business, I often end up at one fundamental business truth. The goal of any business is to make profit. This is achieved by either making more money or reducing costs. Often, business activities are outsourced to experts in order to achieve one of these. For example, I outsource my accounting to an expert, in order to a) ensure that I’m being tax efficient (save costs) and b) because I lack the expertise and the time/desire to obtain it (save costs).

Most traditional outsourcing routes (e.g. accountancy, recruiting, etc.) affect either making more money (e.g. marketing) or reducing costs (e.g. recruiting). Outsourcing research and development is different, in that it can benefit your business in both of these ways.

(In-Person) Harnessing AI With Data, Innovation, and Regulation

Published

Dec 12, 2024

Author

Dr. Phil Winder

CEO

As artificial intelligence reshapes industries, its potential rests not only on powerful algorithms but on the quality of the data we feed it and a clear understanding of regulatory impacts. In this talk, we’ll explore practical suggestions for harnessing data from the perspective of both the public and private sector, addressing data transparency and data sovereignty, respectively. We will also cover trending AI use cases and discuss the potential impact of upcoming regulation.