AI, Cloud, Data & Cybersecurity: A Business Leader’s Guide

We introduce our Cloud Computing training module and briefly discuss a traditional technology model using an example company, in readiness to understand how Cloud Computing works and differs

The first two cloud models are introduced and explained (Infrastructure-as-a-service and Platform-as-a-service), highlighting the key differences to a traditional IT approach, and we show how these could be used by our example company

We explain how Cloud Computing fundamentally differs by outlining five key characteristics that are commonly associated with the approach, also defining areas such as Public Cloud versus Private Cloud

To demonstrate how Cloud services can be setup we have a race between a modern Cloud configuration approach and a traditional data centre installation, highlighting the efficiencies that can be gained

The third and final Cloud model is explained (Software-as-a-Service) and we show how this model, plus all three of those discussed, could be fully applied to our example company

We discuss six areas where Cloud can benefit organisations, and compare them to six potential risk and consideration areas

We discuss how organisations move to cloud, including the Cloud Migration Business Case, Cloud Feasibility Assessment, and introduce a popular framework for assessing which technical routes to consider

Cloud computing usage, background and rationale is reviewed for several well-known companies across different sectors, demonstrating how the majority or major companies today are utilising Cloud, but often in different ways to meet their needs

The module closes with a recap of the topics covered, a brief discussion on Cloud implications for all sizes of organisations through to individuals, and some final thoughts on the future

We introduce this module, define data in a business context, and look at the major areas where data is valuable to an organisation using our CIDER model and several business examples

We discuss some of the key data issues and blockers within organisations, introduce our Data Capability Model aimed at addressing data issues and maximising data value, and talk about an initial focus on Culture and People

Data Governance is explained, and some of the key roles and practices are highlighted that can help organisations progress a data strategy. We also review areas that underpin why many companies struggle to make progress

High quality data is essential to run and develop successful businesses. Our CRUCIAL model is introduced to help explain the key characteristics of quality data and we then look at how organisations go about improving and maintaining that data quality, and reasons why this sometimes still fails

We explain Data Architecture and some of the key practices and common challenges within this field. A business case example is used to compare organisations that have organically grown versus those that have fully considered data architecture and usage (available for download). This lesson helps to explain key areas such as Structured Data, Unstructured Data, Big Data, APIs and Data repositories (Warehouses, Lakes, Marts)

We explain and compare Business Intelligence, Prescriptive and Predictive Data Analytics, introducing and demoing some key tools for each, and showing how in combination they can provide different insights and help drive improved decision making

The module closes with a recap of the topics covered, a brief discussion on what this may mean for all sizes of organisation, and some final key considerations where companies often fail to meet their data strategy objectives. (Our comprehensive Data Capability Matrix is available for download with this lesson)

We introduce the module and define Artificial Intelligence and Business Automation, explaining why these two topics are such a powerful combination. We then present our business use-case scenario that we will build upon in the coming lessons to illustrate the various key concepts as we go

We look at Automated Processes, the first step in our advances in AI & Business Automation. This includes and explains simple Workflow and Robotic Process Automation, applying examples of these tools back to our business use-case scenario

Intelligent Automation is introduced, the second step in our advances in AI & Business Automation. We explain Machine Learning using simple real-world and business examples to review how a machine can learn through three different techniques

We apply Intelligent Automation to our example use-case scenario and then introduce the third phase of advancement - Connected Systems. Within this we explain key areas such as APIs and Services, the potential business use-cases, and then also add this technology to our example scenario

We move on to discuss Advanced Artificial Intelligence, step four in our journey. This introduces and explains Deep Learning, covering how it works, several business applications and some of the key considerations. (A summary of Machine Learning vs Deep Learning use cases is available for download). We close out by applying a deep learning solution to our example use-case scenario

We deep-dive on Generative AI, explaining what it is, and taking time to understand how it works and how it's trained so that you can best appreciate the advantages and limitations of the technology

Having explained Generative AI and how it works in the previous lesson, we now focus on the business application and usage. We discuss how it is used and look at key providers. We review some of the limitations, how additional technical solutions have been introduced to improve accuracy, and explain Prompt and Context Engineering and some key tips to drive improved usage (available for download). Various business uses are discussed (available for download) before we close by applying Generative AI to our use-case scenario

We reach the final step of our automation advancement journey, AI Agents and Agentic AI. We explain these different concepts and illustrate how they can work using a business case example. We talk to some of the tools in this space and when an organisation might consider employing these approaches. Finally, we demonstrate what this could look like in our example use-case scenario

Having used our Customer Support use-case scenario throughout the previous lessons to illustrate the automation and AI phases, we provide four other use-case examples to provide wider overall context. We recap on best-fit principles (summary is available for download) when considering which automation approach to employ and conclude by considering what the future may look like for AI progression

We take what we've learnt in the previous lessons and discuss five key areas where businesses are leveraging AI technologies to gain value. Various tools are introduced and demonstrations provided to highlight some of the features and functions

We summarise the most common AI application uses based on recent studies, against the Ai5 areas from the previous lesson. Given it's prevalence within many organisations, we look at the Microsoft productivity suite and provide some general AI best practice usage tips for individuals to consider

We compare some of the benefits of AI with some of the ethical and usage considerations, before moving into a final recap of everything that we have covered within this module

We introduce the Cybersecurity module, define what it is, emphasise it's importance, and look at some of the main threat 'actors' that pose risks to organisations today

We discuss how people are the number-one route by which cyberattacks occur, and deep-dive on Phishing and Business Email Compromise, explaining what those areas are and looking at some recent examples and common target areas

We move on to look at other threats, starting with explanations and analysis of malware and credential theft, covering real-world examples. We explore the dangers of software vulnerabilities and the differences between zero-day vulnerabilities and zero-day exploits

We complete the list of possible threats by exploring other technical weaknesses and look at areas such as supply-chain attacks. We run through an example to explain Distributed Denial of Service attacks and how they are countered

Having seen how cyberattacks occur, we now focus on the potential outcomes, exploring areas such as theft, fraud, ransomware and business disruption. We look at what hackers may do during an attack and deep-dive on a major real-world example to show the implications

Whilst everyone is potentially at-risk of a cyber attack, we take a brief look at which industries are more commonly targeted and some of the reasons why a particular sector or organisation may be more at risk

We introduce and explain Cyber Resilience, and look at the first set of related considerations for organisations, including security culture & governance and talk through respected industry frameworks that help companies assess and implement cyber security best practices. Other key areas such as incident response plans, training and the principle of zero-trust are explained

We focus on key considerations around users and vendors, explaining key topics such as Identity & Access Management, and important components of that including multi-factor authentication, passkeys and some essential policies

This third and final part of our Cyber Resilience key considerations explains some of the main technology focuses, such as modern security solutions, AI tooling, and network segmentation. We also look at the importance of secure software development and how data is best protected.

Given the importance of many of items discussed in this module, we reiterate some of the key topics in this closing lesson, starting with five areas we believe are important current or future trends to be aware of (available for download). We highlight some of the essential considerations (available for download) for large, medium and small companies, as well as individuals, and close-out with a recap of everything we have covered within the module

In this additional learning lesson, we look at Quantum Computing and the potential threat to Cybersecurity, given the media attention that this topic increasingly receives. We explain cryptography and encryption using a simple example to break down how these technologies work. From that we explain how Quantum Computing may pose a future risk to those technologies, provide views on the severity of that threat, and discuss areas that organisations can consider in order to be best aware and prepared

We introduce the IT Change & Transformation module, defining these areas and discussing their importance and the types of work that they could cover. We present our framework for IT change, SPEAR, a teaching aid that will help us cover the five main topics over the coming lessons, and we touch on the first area of focus, Strategy & Prioritisation

We introduce and define Business Delivery Models, notably a Project Model versus a Product Model, and go on to explain with examples the key differences and use-cases for both, and how in reality some companies may use a mix of models and approaches

The next two stages of our framework are explained, Planning & Preparation and Execution & Delivery. We deep-dive on two popular, alternative approaches for delivering change, Waterfall and Agile, exploring both, comparing the pros, cons and use cases for each and discussing how variants and hybrid methods have evolved too

We continue to discuss the Execution & Delivery stage of Change, and focus on the roles and responsibilities, explaining the key skills and people involved and exploring how they may differ between Project and Product approaches

Change alone doesn't always deliver real value so we look at six steps that can be considered to promote adoption and to help embed change, as the next stage within our framework. We move on to highlight areas where IT Change and Transformation initiatives often fail, and summarise the key factors (available for download) that are observed by companies who successfully deliver Change, based upon industry studies and experience.

We discuss the final stage of our SPEAR framework, Review & Improve, explaining the steps taken by organisations that benefit from continuous improvement. We then compare the framework against three highly popular industry approaches to Project Management and Delivery. By using real-world business examples, we illustrate how in reality many organisations adopt a mix of these approaches, and summarise the key points taken by companies that are able to do that well

We undertake a recap of everything covered within this module before closing out the course with some final messages