Machine Commons Consulting UK 

Introduction

Artificial Intelligence is a broad field encompassing multiple underlying technologies, approaches and platforms. It can be applied in many ways, from autonomous vehicles, medical image diagnosis, stock market prediction, process automation through to its use in conversational virtual assistants such as Alexa and Siri. AI is also a key element in related fields such as intelligent process automation, augmented analytics, virtual reality and more (see diagram below). We characterise these technologies as ‘intelligent technologies’ as they all embed a level of intelligence beyond traditional technologies.

Some AI capabilities are ‘off the shelf’, i.e. embedded in applications or available via cloud services, although most uses of AI require, as a minimum, tailoring to a specific application or organisation. Achieving the full potential of AI though can often still require organisations to create and ‘train’ new solutions using AI approaches such as ‘machine learning’.

In practice, to be successful with AI, organisations need to combine good (more on this later) AI opportunities with an appropriate choice of technology/platform and people who have the relevant skills and experience.

If your organisation, like most, doesn’t (yet) have this capability we’re here to help. We provide insight, guidance and practical support at all stages of your AI journey, from helping with initial understanding through to solution optimisation and AI at scale. In addition to our local team, our alliance with Machine Commons gives us unique access to AI platforms and solutions from over 80 organisations, including a distributed AI team of over 1400 people supplying solutions within over 45 industries.

Learn more below and feel free to reach out to us at mcc@combined-intelligence.co.uk.

AI Journey

AI has the potential to transform how organisations operate, how they interact with and understand their customers and to significantly change the roles and activities of the human workforce. AI also provides the opportunity for the organisation to innovate with new products, capabilities and services.

Realising this potential requires organisations to go on an AI journey (see AI journey for more info), beginning with gaining an understanding of what AI can do for the organisation through to realising the associated benefits at scale.

We can divide this journey into the following stages:

Vision, Strategy and Opportunity

AI has the potential to transform how organisations operate, how they interact with and understand their customers and to significantly change the roles and activities of the human workforce. AI also provides the opportunity for the organisation to innovate with new products, capabilities and services. This potential makes AI an exciting technology for business as well as technology leaders. It’s important though that organisations don’t just try and jump on the AI bandwagon without having a clear view of how this new technology is going to enable them to make a positive contribution towards their overall vision for their business (i.e. growth, scale, employee & customer satisfaction etc).

Organisations need a joined up vision including AI that aligns with and ideally accelerates achieving business goals. A vision that is supported by an effective strategy to successfully realise this vision. This AI enabled vision and strategy should be dynamic, growing and evolving as the organisation achieves success with AI. A key enabler for this being the selection of ‘good’ opportunities, opportunities that are realistic, achievable but also innovative. Unfortunately, AI, like other new technologies, has seen organisations start, with great enthusiasm, new AI projects but then ultimately fail to realise the expected or necessary operational or product benefits. Often due to poor opportunity choices or a flawed strategy.

MCC UK has extensive experience of what can be achieved with AI and how to go about achieving it. We help organisations get their vision, strategy and opportunity choices right.

Realisation

Having selected good opportunities the next challenge is to realise success. Answering key questions, such as:

Frameworks, Platforms and Solutions – There are many AI frameworks, platforms and solutions available, is the right choice to go with an existing solution and tailor it to the organisations needs or is a new custom solution built using machine learning frameworks the right approach (or even a mix of approaches)?

People/Skills – Does the organisation have its own in-house capability, does it want to build/extend one or is the best approach to use a partner with the right skills and experience (perhaps even a hybrid approach)?

Lifecycle – AI needs a project lifecycle that supports the research, development and operational phases. A lifecycle that includes a strategy to go from early stage proof of concept through to robust and scalable live solutions (a challenge which many organisations struggle with). This lifecycle needs to be specific to AI as traditional IT or software project lifecycles won’t work. Does the organisation appreciate this and have an appropriate lifecycle covering governance, project management, communication, MLops, benefits realisation etc etc?

There are many of these types of questions that organisation need to answer in order to achieve success with AI. These answers aren’t the same for every organisation and will vary dependent on the specific type of AI being applied. The scale of the Machine Commons collective enables us to embrace this diversity and to call upon the right specialists and solution providers to provide the optimal answers.

Operation and Optimisation

The AI world is littered with AI projects that achieved proof of concept success but then failed to achieve the same level of success or performance in operational use. With AI, it’s also important to have a strategy to maintain and ideally optimise performance levels. Over time input data can change, requiring the ‘trained’ AI solution to be ‘retrained’ in order to continue to meet performance expectations. Additionally optimisation can be achieved by analysing the live performance of the solution and using solution errors to generate extended training sets which, when used, can reduce errors and improve overall performance.

The AI solution will often soon become a business critical component of the organisation’s enterprise architecture or product feature set. This then requires the organisation to put in place the ability (internally or externally) to perform support and maintainance activities within appropriate turnaround times.

Even where organisations achieve live success with AI, transitioning to using AI at scale across the business is another significant challenge. Not only are there technical and business issues in achieving this, there will be challenges related to people, skills and organisational culture.

It’s important that organisations consider and plan for all these operational, optimisation, support and scaling issues rather than leaving them as after thoughts. With have the experience to guide you through this process. Many of Machine Commons partners also offer managed solutions that are cloud hosted and supported 24×7. 

If you’re interested in talking to us about any of the above or you think we could perhaps help your organisation please get in touch by emailing mcc@combined-intelligence.co.uk.