How organizations can benefit from a new alliance between humans and machines

Bringing people and technology together

In the first article of our hyperintelligence series, we looked at the history, development, and progress of AI – and how it is creating new opportunities for organizations.

In article two, we introduced a simple framework to make AI more accessible to all of the individuals within an organization by comparing AI to the five senses of human intelligence.

In this article, we will consider how AI technologies are also creating new opportunities for individuals in the workplace.

In the age of hyperintelligence, it is not just about what activities people can complete based on their own knowledge – it is also about how they use their skills and experience to access and apply knowledge available on their organization’s intranet or the global internet to create value.

This is leading to a fundamental shift in the roles of individuals and managers that suggests organizations should consider transforming their operating models to match the “Five Senses of Intelligent Automation.”

Enhancing the role of the individual

A powerful new alliance is emerging between the individual and technology. Machine intelligence is augmenting human intelligence and expanding the limits of what individuals can achieve. This is liberating people’s time and allowing for more choice and creativity in the workplace.

Machines can do certain activities quicker and more accurately than people – such as processing and analyzing data. This revolution is less about doing the same things cheaper or completing activities faster, and more about freeing people from tasks better suited to machines. It enables people to augment their skills and knowledge and to rebalance their workload – such as taking more time to focus on driving insight and determining the next best action, rather than populating and manipulating spreadsheets.

The era of the “Google worker”

Until recently, people have generally required personal knowledge to generate value for the business – or been reliant on the willingness of managers to share their skills and experiences.

Knowledge is now more open and accessible to everyone. We all use the likes of Wikipedia, online dictionaries, and YouTube to develop new skills and tackle new challenges with confidence. We no longer need to hold knowledge in our memory, but to understand the relevance of the information we find. Improvements in connectivity are also creating networks that facilitate closer collaboration with different people, which is broadening our effective knowledge.

As such, people at work are becoming less concerned about what they know, and more interested in developing new skills to identify opportunities and solutions that will deliver value. Traditional workplace boundaries are disappearing. Individuals are resetting their expectations for what they are able to achieve. Individual knowledge is less of a differentiator when it is stored in a database and readily accessible through a search engine. There are fewer limitations and far more opportunities. As long as they are delivering value, people can apply their creativity and act on their ambitions like never before.

Across all industries and services, we are going to see a new generation of Google workers emerge – people who proactively use AI tools to enhance and augment their skills and knowledge.

Established training and education will need to change radically to enable and encourage this release of potential. Managers will need to adopt a new approach to support their teams, and organizations will need to consider new operating models.

Rethinking the role of managers

In the age of hyperintelligence, where the role of the individual has changed significantly, it follows that the way they are managed and measured must also be revised.

Managers of the future will continue to be valued for their own individual contribution and that of their team. However, the measures of that contribution will change to include things like:

  • Value added to the organization and its customers
  • Behaviors exhibited (more creativity and innovation)
  • Leadership demonstrated to drive change.

They will have to embrace the age of the Google worker to create synergies within teams and juxtapose different skills to create differentiation.

The role of the manager will be about encouraging, supporting, and enabling individuals, exploring new ways to engage them and helping identify the greater contributions they can make to the business.

Less supervision, more trust

The relationship between manager and individual will change too. Rather than instructing people how to work and looking over their shoulder to ensure they have remembered, managers will need to let go and trust them to find their own answers. They will still need to hold people to account for their performance, but the focus will be on outcomes achieved, rather than traditional metrics such as attendance and efficiency.

As people adopt AI technologies to augment their performance, the organization will start to depend on more valuable contributions from them. Therefore, the fundamental purpose of a manager will evolve to be the enabler of change, as well as stability, within their environment.

Shaping the organization around the “Five Senses of Artificial Intelligence”

Legacy businesses are traditionally organized around core functions such as customer services, finance, HR, and supply chain, with tasks and data managed in silos. However, by adopting a new operating model that’s organized around the “Five Senses of Intelligent Automation,” better connections can be formed within and between those functions to create a hyperintelligent enterprise.

As we have seen, knowledge is key to hyperintelligence. It needs to be consolidated into one central function, rather than being spread across different teams. Improvements in ownership and accountability lead to clearer governance and control, resulting in enhanced integrity and quality of knowledge, enabling better and quicker decisions. This is the approach that “native” AI companies such as Amazon and Google take.

Native AI companies also employ various monitoring functions that track their employees’ use of knowledge as well the demand, questions, and feedback from their customers. An example is the use of HTTP cookies, which track browsing activity and provide companies with a greater understanding of what people are looking at over time to enrich their knowledge base.

This knowledge is then fed into models that analyze customer activity and predict future purchasing decisions. This insight may result in communication with the customer to recommend a combination of relevant, complementary, and substitute products or services.

If this leads to an order, it will be routed to the relevant supplier and fulfillment partner to act appropriately to meet the customer’s requirements.

AI at work – demand-driven knowledge

At Capgemini, we are using a corporate knowledgebase to support 15,000 associates who deliver Finance & Accounting services. This has benefits for people, managers, and overall business outcomes:

  • Individuals can complete their tasks with reliable knowledge and are no longer constrained by their ability to remember or their manager’s willingness to share the right training. Work instructions are easy to locate and rated for their ease of understanding, allowing individuals to explore new areas and learn faster.
  • Managers have increased confidence knowing that their teams have reliable information, and they also benefit from clear visibility on what their people don’t know. Seeing what questions are trending and the root cause of those trends allows managers to create effective training interventions and identify latent problems in performance or disruption in the client environment.
  • The organization has increased confidence that the right knowledge is being deployed effectively, and that knowledge is no longer dependent on specific people. Better management of knowledge leads to improved client satisfaction and new services.

Hyperintelligence – step by step

Although it is unrealistic for most legacy companies to transform overnight into a native AI company, they can take a step-by-step approach to hyperintelligence that will help them stay competitive. This could start with the formation of a single function responsible for all of the knowledge in the organization.

For example, we’ve worked with a leading biotech company to put stronger governance around all of its master data. This ensured that critical knowledge was firstly cleansed and is now managed and enriched centrally, improving completeness, relevance and quality. There is now an organizational trust in the integrity of the corporate knowledge platform that allows timely, informed and aligned decisions to be made with confidence.

Keeping it simple

Organizations in the initial phase of transformation can learn simple lessons from the early adopters as they go about reshaping their operating models to support hyperintelligence:

  • Think technology and people – AI is bringing benefits to all areas of business, and is transforming (rather than replacing) the role of people. Consider how technology will shift the skills your people need.
  • Be inclusive – involve a broad group of stakeholders as you start your AI journey, so you can factor in all the different implications for people, managers and organizational functions.
  • Measure impact – thanks to the reducing cost of automation technologies, you can start valuing people on metrics such as customer satisfaction, rather than attendance and efficiency.

In our next article, we’ll look at the flexible infrastructure that underpins AI and how it is widely accessible today, enabling businesses to implement their own solutions quickly and without deep technical expertise.