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Priming Your Organisation for AI Success

Propel Artificial Intelligence in your company with four preparatory steps


You know data is important and a data-driven strategy is crucial to achieve greater impact in businesses. And you may have started to look into signs where you need changes immediately. However, your team is not aware yet how to bridge the gap between the now and the ever changing digital transformation that you are embarking on. Since navigating our world after the explosion of data is, after all, a complex journey, we suggest you step back into analysing your current strategic goals and their alignment with your data and AI strategy.

To best prepare your journey towards formulating strategic direction for your data-intensive use cases, it is important to first prime your organisation with the following four steps  your team to feel ready, easily track progress and evaluate outcomes.


To the moon framework_Machinemind

Scout your resources

Resources are the foundation in the journey to move your organisation towards your strategic goals. And in this case, your data, IT infrastructure, financial budget and personnel should be in good order. Your IT infrastructure should be modular enough to integratenew AI applications swiftly. It should also have a high capacity for AI-related, data-intensive training and testing, which is equipped with the ability to store, process and transport or stream large amounts of data. Speed and scalability of computing powers must be in place to handle extensive workloads.

Next, ensuring your financial budget is strategically allocated for AI adoption to support the overcoming of initial obstacles and uncertainty. The lifecycle of data-intensive applications consists of tailoring an AI system towards an organisation’s unique context and data. Therefore, the adoption process also requires organisations to invest in establishing new playbooks and overcome initial trial and error on AI capabilities and their value.

And finally, make sure that tech specialists and business analysts are assigned to collaborate in the   adoption process. Business analysts often understand AI capabilities in an abstract manner, as well as its domain know-how. On the other hand, tech specialists have dedicated data and AI-related skills and can develop specific solutions. Together, they can facilitate use case discovery and be the bridge between business functions and AI models.

Evaluate your skills

How is your team interacting with and handling data right now? While they might be aware of the importance of data, it is crucial for an organisation to have the right skills and understanding of ethical issues with data and AI adoption. People should also be holding the right roles to equip them with this new future of work in a data-driven world. Are they able to read, work with and analyse data, and communicate with data?

To best ensure your organisation is well-equipped to handle incoming mountains of data, evaluate them based on some of the following questions:

  • Are they able to use different tools to work with data?
  • Can they set up and minimise data pipelines in a database?
  • Can they analyse the data by inspecting, cleansing, transforming and modelling it to achieve our business goals?
  • Are they capable of data storytelling?
  • Overall, is the team staffed with sufficient data-related roles?
  • Does the team have adequate understanding and expectations toward data and analytics (such as ML/AI)?
  • As you have the skill-related assessment from the team, you can decide the level and variety of education required to equip them best in adopting data and AI.

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Refine your strategy

Your data and AI strategy is about using data and AI in ways that help the business to meet strategic goals. As it’s very easy to get confused by what ‘can’ be done, we need to focus on what data and AI  ‘should’ do for your overall strategy. Without this focus, you won’t generate return on investment and your project will be costly and probably achieve very little.

When you understand the interplay of top management support, business potentials, user and process fit, you will be able to keep your data and AI strategy in line with your overall business strategy.

Top management support is very crucial to kick off the adoption process. They need to signal, communicate and actively engage with the transformation to foster the data and AI initiatives. The leadership team will need to embark on the journey first, and bring in the teams to integrate this into the day to day tasks.

As a joint effort, you should develop a common understanding of the business potentials and how it is beneficial, suitable, and generates value for your organisation and end users. Customers or end users are key to envision where the business directions will go. And it is your strategic decision how they benefit from resourceful data and a great AI design.

Foster your innovation culture

Bringing your data and AI strategy to your organisation requires teams, business decision makers and stakeholders to be actively involved in the process, and therefore, have the right set up and mindset to start with. While it is valid to print -driven values, mission and culture statements on your walls, the company must embody the data culture, day in, day out.

This also includes how the teams on every layer of your organisation are encouraged to recommend and make decisions based on data. Never forget that the human factor is the centrepiece and foundation of implementation. After all, a successful ecosystem emerges from the grass roots.

Collaborative work and flexibility towards change hold a big role in  the adoption process. Both will help your team to engage as one entity to develop the skills and resilience in finding the alignment within the organisation.

Next, assess your team’s level of confidence in embracing innovativeness – a ”trial and error” culture. Ask how your organisation plays the rewards and recognition to encourage the talents to stay actively engaged in the journey.


Connecting it all

It is undeniable that data is becoming a critical business asset, and that it is revolutionising the way businesses operate across a wide range of industries and sectors. Every organisation, regardless of its size, is now required to operate as a data-driven company. Every company requires an effective strategic direction for data and AI, especially if it is a data-driven business.

If you have checked these four pillars off your list, we can help you in the next step: to put words into action and get started. Reach out to us if you would like to know more about our Roadmap Programme.




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