News Analysis
The Gist
- Green shift. Sustainable AI is crucial for CX leaders balancing innovation and environmental responsibility.
- Eco concerns. AI environmental impact is a growing issue, affecting both operational costs and brand image.
- Power alert. AI energy consumption is skyrocketing, posing long-term challenges for businesses and the planet.
As artificial intelligence (AI) becomes ubiquitous, transforming sectors from healthcare to customer service, it's high time we confront a glaring but often ignored problem: AI's voracious energy appetite. For CX leaders who are betting big on AI to redefine customer experiences, overlooking this concern is not an option anymore. Today, let's unpack some sustainable AI ideas and discuss how CX leaders can balance its benefits with environmental responsibility.
Unlocking Hyper-Personalization: AI's Pivotal Role in Tailoring Customer Experiences
By understanding customers on an individual level, brands can curate personalized content and offers in the moment that resonate deeply.
Hyper-personalization leverages real-time data and AI to deliver tailored experiences that go beyond traditional segmentation. With hyper-personalization, Netflix, for example, dynamically fine-tunes movie recommendations for each user based on their viewing history and habits. Similarly, ecommerce sites such as Amazon customize prompts and product suggestions using predictive analytics.
With new applications seemingly every day, AI can have an impact across the entire customer lifecycle. "From customer self service using question answering bots to a more personalized experience by monitoring signals from the customer’s 'digital body language' and presenting variations of messaging optimized through machine learning, AI will significantly improve customer experiences," said Seth Earley, CEO at Earley Information Science, an information architecture consulting & services provider.
CMSWire’s 2023 State of Digital Customer Experience Report revealed that 45% of CX professionals believe that AI and machine learning will have the most impact on customer self-service, followed by gaining actionable customer insights, freeing up staff to engage in high-level tasks and improving customer retention.
The key ingredients enabling this are automation, machine learning and access to rich customer data. AI systems can rapidly process the massive amounts of information that are needed to uncover micro-segments of one. They can then automatically tailor messages and product recommendations specifically for each customer, even anticipating their future needs.
The business value is clear: Hyper-personalization boosts conversion rates, revenue and customer lifetime value. For industries dependent on 1:1 relationships like banking and insurance, it is immensely impactful. AI-driven hyper-personalization creates experiences so customized that customers feel understood and catered to before even asking.
“Personalization at scale is the holy grail of CX achieved through contextualizing information based on who they are, where they are in their journey and dozens of other factors,” said Earley. “These might include for example, level of technical proficiency (if a technical sale) or their style preferences (for a clothing or accessory type of sale).”
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The Staggering Energy Costs Powering AI's Rise: Is There a Sustainable AI Solution?
The energy demands of AI are escalating at an almost alarming rate. By 2027, data centers for AI could even outstrip the entire electricity consumption of countries like the Netherlands. A recent report from the International Energy Agency indicated that globally, data centers currently account for 1 to 1.5% of global electricity use.
A 2021 report from the U. S. Environmental Protection Agency (EPA) indicated that approximately 62% of the world’s electricity comes from burning fossil fuels, the production of electricity generates the second-largest share of greenhouse gas emissions. When these statistics are combined, they are indicative that if nothing is done to mitigate the ecological damage that occurs from this use of energy, rather than positively impacting the global population, it could help seal its fate.
The rise in electricity consumption due to AI is not just an environmental concern — it's a looming operational and financial challenge for businesses. Data centers, the backbone of AI operations, are becoming veritable power guzzlers. If projections hold true, these centers alone could consume as much electricity as entire nations within a few short years.
So, what's driving this? One major factor is the production and usage of energy-intensive hardware. Consider NVIDIA's DGX chips, for example, designed to accelerate AI workloads but also requiring substantial power. By 2027, NVIDIA envisions shipping 1.5 million AI server units per year, and when these servers are running at full capacity, they would use a minimum of 85.4 terawatt-hours of electricity annually.
The energy demands of data centers go beyond just powering servers; they extend to complex operational needs like cooling systems and backup generators. Traditionally, data centers relied on air-based cooling systems, which not only consumed a lot of energy but also required a complex infrastructure. However, a newer approach called immersion cooling is gaining traction. In this method, server components are submerged in a special, non-conductive fluid that dissipates heat directly. This not only cuts down on energy usage but also reduces the physical size of the data center. Immersion cooling is presenting itself as a potential solution to the multifaceted challenge of energy consumption in data centers.
Related Article: What Sustainable Marketing Means for the Conscious Marketer
The Nuclear Option
Besides immersion cooling, brands are considering all viable options for dealing with AI’s vast energy requirements. Microsoft, for instance, is considering the use of small nuclear reactors to power its AI and cloud data centers. Although the tech giant hasn’t made any announcements regarding the controversial energy source, they recently posted a job listing stating that they are looking for a Principal Program Manager Nuclear Technology whose job it would be to “assess how nuclear energy could be used to power the data centers hosting AI models.” The role will also “be responsible for maturing and implementing a global Small Modular Reactor (SMR) and microreactor energy strategy.”
Implications for Customer Experience Management
As the use of AI becomes increasingly embedded into customer experience services, the energy costs of running these data-intensive operations are inevitably going to be passed down. The implications for CX are multifold. This financial ripple effect poses questions about the long-term sustainable AI and ROI of AI-powered CX initiatives.
Earley suggested that cost to compute will always be a factor in any AI powered model. “That subsumes energy costs and may push organizations to less costly open source LLMs. Training the model is the largest energy and computational expense but there are easier ways to achieve the benefit of ChatGPT types of applications without incurring that cost by not attempting to retrain the model but adapt it with approaches like Retrieval Augmented Generation.”
Beyond the financials, there's also the pressing need to align with sustainability goals, an agenda that's quickly moving from peripheral corporate social responsibility to core business strategy. For senior CX leaders, this is a crucial time to recalibrate strategies. One pathway could be through exploring more energy-efficient AI solutions. Alternatively, taking the lead in advocating for sustainable energy policies within the brand can also be a significant step forward.
Sustainability has become a critical point of differentiation and core value for brands as ecological awareness grows worldwide. Customers increasingly expect companies to adopt ethical practices that align with their own ideals. AI and data centers present a dilemma, as their immense computing power enables transformative innovations yet requires substantial energy. Brands leveraging AI have a responsibility to mitigate their environmental footprint through renewable energy sources and optimized efficiency.
Those brands that are making sustainability an integral part of their culture rather than an afterthought stand to benefit from heightened customer and employee affinity. By tackling sustainability challenges head-on, brands can transform an obstacle into an opportunity to lead by example. The brands that do this most effectively will earn customer and public trust through their commitment to building a greener future.
Balancing AI Advancements With Environmental Sustainability
As we forge ahead into a future where AI's role in customer experience is only expected to grow, striking a balance between technological innovation and environmental responsibility is crucial. This could take the form of industry collaborations focused on developing sustainable AI technologies, or perhaps the creation of organizational sustainability task forces that include key CX stakeholders.
While AI promises immense benefits, we must innovate responsibly and minimize any potential downsides. Brands should look for opportunities to minimize the environmental impact at each phase of the AI model lifecycle. For example, training large AI models requires vast computing resources, so brands could optimize data preprocessing to reduce training data size. When deploying AI systems, prioritizing efficiency and leveraging "green computing" practices can cut energy consumption. Setting up regular model monitoring and maintenance can prolong usefulness and reduce the need for retraining.
On a broader level, establishing cross-functional teams focused on AI ethics and developing companywide green AI policies are important. Seeking out renewable energy sources to power data centers and cloud computing can also make a significant difference. Industry collaborations dedicated to advancing and standardizing sustainable AI practices will be key. With proactive efforts to make AI more ecologically conscious, brands can uphold their values while delivering next-level customer experiences powered by leading-edge innovations.
Baking Sustainable AI Energy Practices in From the Start
As we witness AI's transformative impact on customer experience, the energy considerations are too significant to be relegated to a footnote. CX leaders have a vital role to play in addressing these challenges head-on.
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By proactively incorporating energy needs into sustainable AI adoption roadmaps, businesses have the opportunity to not just revolutionize the customer experience, but to do so in a way that is both sustainable and responsible.
