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What does it mean for every company to be an AI company?

Peter Marrs
Peter Marrs  • 5 min read
What does it mean for every company to be an AI company?
Every organisation needs a training regime that will set the right foundation for AI deployment. Photo: Pexels
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We are familiar with the adage “all companies are technology companies”, but with the acceleration of AI adoption, the new version is “all companies are AI companies”.

According to Dell Technologies’ latest Innovation Catalyst Research, in the Asia Pacific and Japan, 85% of respondents believe AI will significantly transform industries, and 52% have already implemented generative AI in their organisations. Whether a business has been an early adopter of the technology or is still assessing the right time to enter, preparing for AI deployment is an unavoidable future that needs to happen soon, given the pace of AI’s development.

Getting fit for the AI game

AI deployment is like being on the starting line of a long-distance event. Before stepping onto the start line, much preparation must be done. While not all companies need to adopt AI immediately, there is an argument for at least embracing an AI-centred mindset and beginning to align their technology strategy immediately.

Every company will be an AI company, it’s a question of when and how, not if. When they are ready to adopt AI in a way that makes the most sense to their business and brings the most value, their mindset and readiness will mean they will be ready to harness its possibilities.

Regardless of where the business is on the scale of adoption, the “training regime” will set the right foundation for AI deployment. The following are key to achieving that.

See also: Achieving true digital transformation: It’s not the tools, it’s the people

Adopting a visionary and collaborative approach

Leadership with forward-looking strategies addresses what AI adoption means to the business and will guide and align teams using AI to achieve strategic goals. At Dell, for example, we have defined a strategy detailing our AI approach, which is focused on opportunities within four areas: AI-In, AI-On, AI-For and AI-With.

The approach should be mapped against a communicated strategy that carefully considers the current and future readiness of the business in terms of talent, skills and resources.

See also: How tech companies are retaining female talent in Asia Pacific (Part 2)

Developing a comprehensive playbook outlining the approach, key considerations and realistic goals against a business roadmap is needed to align people, processes and technology toward common goals in AI implementation.

Finding the ‘language’ for impact measurement

A framework for demonstrating a tangible return on investment to communicate its impact and communicate it effectively to stakeholders is key.

By establishing a shared language and aligning on a set of success outcomes for measurement, all stakeholders can fully understand and appreciate the value of AI. Leaders can look to quantify “mileage” metrics of productivity and efficiency boosts in the form of cost savings, faster time-to-market leading and revenue growth to show proof of concept.

Identifying realistic use cases

Integrating new technologies into businesses requires careful consideration due to the inevitable trade-offs between potential benefits and resource constraints.

To maximise investments, business leaders can identify one or two realistic, practical and high-impact use cases to kickstart AI deployment, carefully assessing these pilot projects against previously established measurements such as scalability, ease of use, quality and accuracy to decide on scaling projects. The key step is to do so in an iterative manner, refining the approach and staying adaptable to the ever-changing AI landscape.

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Encourage education and experimentation

Dell’s Innovation Catalyst Research showed that half of the Asia Pacific and Japan respondents are uncertain of their industry in the next three to five years.

Gaining a deep understanding of the practical applications of AI in the context of your own business through a safe “sandbox” experimental environment thus becomes a crucial first step in exploring its possibilities and assessing use cases in a controlled manner. The starting point is establishing that sandbox, even if the business won’t deploy its outcomes immediately.

Establishing governance and ethical guidelines

Definitive boundaries, regulations, and processes for a structured and considered approach to experimentation are needed while adapting to the changing regulatory landscape around AI. Regulations cannot be a surprise when the business begins to engage AI in any form.

The ‘AI company’ has a set of ethical guidelines that align with the organisation’s values to build trust with customers, employees, and stakeholders while trialling new technology.

Compliance ensures that measures are taken to reduce common issues in AI, such as bias and lack of transparency.

Even if an organisation hasn’t adopted AI specifically, it will interact with AI in some form, so a policy will guide all such engagements.

Preparing for the AI start line begins with solid training

Every company will be an AI company. Today, stepping up to the AI deployment “start line” is not the beginning but a major and necessary milestone in the journey.

Beyond that, we will see AI-first businesses use AI to strengthen their competitive advantage, and those that focus on understanding and solving business problems aligned with these guidelines will win the race.

Peter Marrs is the president for Asia-Pacific, Japan and Greater China at Dell Technologies

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