Reinvention in the Age of Generative AI
10-minute read
In Brief
Disruption is on the rise and reinvention is becoming the default strategy for success in turbulent times.
Reinvention works, and reinventors are pulling ahead of the pack, creating an imperative for others to act.
Generative AI represents a clear opportunity to accelerate reinvention and close the performance gap.
We see five imperatives the C-suite must address to reinvent in the age of generative AI.
Reinvention is the strategy for success
We predict that over the coming 12-24 months there will be a significant uptick in companies who embrace generative AI as a catalyst for reinvention.
Why is generative AI different from other technological innovations we’ve seen in recent years? This technology has the power to reinvent every facet of an organization. This is new. Through our work, we see empirical evidence that this trend is already in motion, particularly as generative AI rapidly disrupts every industry.
Disruption meets its match
Organizations are still operating in an unsettled landscape. The annual Accenture Pulse of Change Index found the rate of change affecting businesses has risen steadily since 2019 — 183% over the past four years. In response, 83% of organizations have accelerated the execution of their transformation since last year.
Disruption is up 33% year-on-year
Accenture Pulse of Change: 2024 Index
Reinvention landscape
Many organizations are keen to reinvent — some are further along in their journey than others.
A small number of “Reinventors” (9%) have already met the high bar of building the capability for continuous reinvention. They’re making swift progress in executing their strategy and setting out to define a new performance frontier with technology at the core of their reinvention journey.
Among the largest companies, especially those with revenues over US$50bn, the number of Reinventors has quadrupled in the past year. Industry giants are not standing still. Unlike the digital revolution, the largest companies are taking an early lead, leveraging their substantial investment in building their digital cores and talent. Two industries saw double-digit increases in the number of Reinventors: in software and platforms the figure is up 34 percentage points to 43%, and in life sciences it’s up 13 percentage points to 20%.
Most organizations are still at the beginning of their reinvention journey, with few reinventing at scale today. Similar to last year, the majority (81%) are “Transformers.” Transformers should keep going. They are taking many of the right steps toward reinvention — however, they are less likely to be building sustainable capabilities to reinvent continuously and may be missing the speed and cost efficiencies from a connected strategy of reinvention. And we see a financial performance difference, with Reinventors pulling ahead. The remaining 10% of “Optimizers” are organizations where reinvention isn’t currently a priority.
Reinventors are creating an imperative for others to act.
We expect Reinventors to grow the value gap significantly in the next three years.
Source: 2019-22 = CAGR based on actuals. 2023-26 = self-reported expectations from the Accenture reinvention survey, stress-tested vs. analyst expectations.
Why generative AI shouldn’t be underestimated
In the past several decades, we haven’t seen any other technology with the potential to materially impact every aspect of a company — this is why we connect generative AI and reinvention. The only way to realize generative AI’s full potential is to embrace the need to reinvent processes and talent, while managing the technology through a new capability commonly referred to as responsible AI — and with a digital core that has a data and generative AI backbone.
Generative AI has become an extraordinary force in enabling reinvention and accelerating organizations’ progress toward a new performance frontier. Some understand this potential and are taking action. We’re seeing this among Reinventors, and also among a group of Transformers that we expect to leapfrog today's leaders by applying generative AI more intensively to their business.
What Reinventors know:
Generative AI is unique in its ability to impact the entire value chain and to drive productivity and growth in a way that establishes a new performance frontier.
Achieving reinvention through generative AI is only possible by developing end-to-end business capabilities, rather than the more common function-by-function focus on individual use cases.
Developing end-to-end capabilities requires extensive and coordinated changes across processes, people and technology. Processes need to be redefined, people need to be reskilled and a data and generative AI backbone needs to be built into the digital core.
Generative AI in action
3M hours saved
A government agency responsibly used the latest digital technologies to deliver automations at speed and scale, saving three million operational hours.
16M customer offerings
A bank delivered 16 million hyper-personalized offerings to customers within three months of building a generative AI-powered marketing solution.
+10% revenues
An insurer is reinventing the entire workflow of underwriting with the potential to increase revenues by 10%.
Reinventing today to lead tomorrow
Generative AI represents a clear opportunity to accelerate reinvention. Based on delivering more than 700 generative AI client engagements and our research, we see five imperatives that the C-suite must address to reinvent how their businesses operate. We explore these imperatives, showcasing examples from our clients to illustrate them.
Five imperatives for the age of generative AI
1.
Lead with value
2.
Understand and develop an AI-enabled, secure digital core
3.
Reinvent talent and ways of working
4.
Close the gap on responsible AI
5.
Drive continuous reinvention
1. Lead with value
Shift the focus from siloed use cases to prioritizing business capabilities across the entire value chain, based on an objective assessment of the business case, enterprise readiness and the corresponding return on investment. Companies can pursue generative AI investments in two categories: "no regrets" investments that offer productivity improvements and "strategic bets" that offer truly novel competitive advantage including reshaping how industries operate.
Action 1
Understand the potential to reinvent your value chain and develop end-to-end capabilities powered by generative AI and new ways of working.
Action 2
Be value-led in every business capability you choose to reinvent with generative AI.
Action 3
Identify strategic bets where the technology creates differentiated sources of value that can’t be easily captured by competitors.
Action 4
Reorient your organization from siloed functions to end-to-end business capabilities and decision-making through a unified data architecture and cross-functional teams.
Roche: Dissolving boundaries to deliver data-driven cancer care
Realizing the potential for tailoring care to each person requires a new way of working that breaks down barriers across the lifecycle of care that a patient receives. Roche is building platforms that aggregate data from disparate sources. One such platform is its oncology hub, which securely makes sense of all patient data and gives clinicians a central workspace for collaboration. This helps to get patients into treatment faster in a field where time can save lives.
2. Understand and develop an AI-enabled, secure digital core
Companies need to elevate IT for the age of generative AI. Connect disparate data sets and technologies via an AI-enabled, secure digital core. Generative AI requires a fundamentally different enterprise architecture in which data is more fluid, and unstructured and synthetic data become much more important. It places higher demands on infrastructure, and IT operating models will need to change. Reinventors prioritize their digital core as a key competency.
Watch for our upcoming research on the digital core later this year.
Action 1
Understand what “digital core” means for you and look at your technology objectively to understand where your digital core is — relative to the industry, and most important, relative to what is needed to use generative AI.
Action 2
Understand the new capabilities required for a data and generative AI backbone and what it will take to build them.
Action 3
Ensure your CIO is embedding cyber security practices early in the lifecycle across technology and that you have a strong security culture to prioritize resiliency.
Action 4
Understand your current technology and advisory ecosystem, and refresh your strategy on how you will work with them to compress the reinvention cycle.
Action 5
Rigorously measure the progress toward ensuring more than 50% of your technology investments are targeted at building the new.
Southeast Asian national oil company: Simplifying volumes of data
This client has huge volumes of data in different formats — and generates more daily. After taking a holistic look at the issues, it deployed generative AI and cognitive search to realize the true value of its data and drive new growth. Its new knowledge base incorporates more than 250,000 documents with structured and unstructured information, surfaces the desired information and converts it into a chosen format. The new, integrated setup makes information discoverable with minimal effort, automates the knowledge-gathering process for different roles across the organization and helps reduce accidents.
3. Reinvent talent and ways of working
Success with this latest tech revolution requires leaders to set and guide a vision for reinventing work, reshaping the workforce and preparing workers for a generative AI world. Companies must quickly clarify how work needs to be reinvented and reshape the workforce accordingly. This will require skills-based HR and continuous learning across all levels of the workforce, including the C-suite. Success requires putting people at the heart of change, and it will mean leaders with different skills. As leaders acquire necessary new skills for the age of generative AI along with the workforce, they can better drive reinvention across entire value chains and business processes.
Action 1
Create a talent strategy that identifies how work will change, documents the impact to roles and assesses what skills are needed for every generative AI use case.
Action 2
Build strong people-centric change competencies that are the same across functions and business processes to fully understand the impact of generative AI on people and their experiences.
Action 3
Develop, either organically or with partners, the continuous learning capabilities needed to support reinvention. Prepare workers for generative AI, actively involving them in change and ensuring they have market-relevant skills.
Action 4
Review HR capabilities and invest in the competencies and technology needed to support the reinvention vision. HR is a core part of the business strategy.
Action 5
Review your employee value proposition and ensure that it makes employees feel Net Better Off for working at your company, and that your use of generative AI is consistent with your commitments.
Biopharmaceutical company: A reinvention to match its ambition
Aspiring to be the premier research-intensive organization specializing in the science of discovering and developing new therapies, this client is developing new types of leadership training and experiences to help foster the entrepreneurial mindsets and new ways of working that support its ambitions. This includes involving people properly in the design process, a program to upskill thousands of people to make them experts on generative AI, and bringing in the right talent at the right times.
4. Close the gap on responsible AI
Design, deploy and use AI to drive value while mitigating risks, including bias and harm, liability and compliance, unreliable outputs, confidentiality and security, sustainability, and workforce transition. Given generative AI’s speed of evolution and adoption, these risks need to be a focus now to avoid challenges later, including regulatory costs. The vast majority (96%) of organizations support some level of government regulation around AI, but just 2% of companies have self-identified as having fully operationalized responsible AI across their organization. Closing the gap requires a plan that moves from commitment and frameworks to action on the ground.
Action 1
Agree and adopt responsible AI principles with clear accountability and governance for design, deployment and usage of AI.
Action 2
Conduct AI risk assessment. Understand the risks of your organization's existing AI use cases, applications and systems through qualitative and quantitative assessments.
Action 3
Perform ongoing, systematic testing of AI for fairness, explainability, transparency, accuracy and safety using the best available tools, and enable mitigations.
Action 4
Establish ongoing monitoring of AI systems and oversee responsible AI initiatives while executing mitigation and compliance actions.
Action 5
Engage cross functionally to address workforce impact, compliance with laws, sustainability and privacy and security programs across the enterprise.
Monetary Authority of Singapore: Operationalizing a ground-breaking responsible AI program
The Monetary Authority of Singapore (MAS) is one of the first financial regulators to have a responsible AI program. MAS established Veritas, an industry consortium, to help financial services institutions (FSIs) evaluate their AI and data analytics solutions against the principles of fairness, ethics, accountability and transparency. A core team within Veritas developed a methodology framework to operationalize those principles. This helps FSIs gain value from AI responsibly while building a fairer future for billions of consumers worldwide.
5. Drive continuous reinvention
Change is constant, so reinvention never ends. Leaders cannot approach reinvention as a contained effort undertaken every few years. They must build the capability to continuously reinvent. Enterprises that not only survive disruption but come out on top are those that are in perpetual motion. Companies must constantly build their organizational agility. It’s a switch to a state of openness to new thinking, requiring a cultural and operational mindset for continuous change, powered by a flexible digital core that supports generative AI at pace and at scale.
Jack Azagury, Group Chief Executive – Strategy & Consulting
Muqsit Ashraf, Lead – Strategy
Oliver Wright, Senior Managing Director – Consumer Goods & Services, Global Lead
Karen Fang Grant, Global Research Lead – Industry Networks & Programs
Mike Moore, Principal Director – Accenture Research
Source: https://www.accenture.com/us-en/insights/consulting/total-enterprise-reinvention