The rate at which generative AI is advancing is creating angst and excitement across the business community as opportunities for its use evolve daily.
Initially, AI was seen as a helpful tool that could speed up the rate at which some type of menial work was undertaken, but now, it seems there is genuine worry that AI is going to take people’s jobs away.
We are seeing incredible leaps in the use of AI for creative activities such as imagery for marketing, advertising and communications. Based on this, there is no doubt that AI could replace knowledge and creative experts faster than customer service personnel.
Since OpenAI launched its widely publicised bot ChatGPT late last year, there has been speculation that the generative tech will enable businesses to do away with people and cut costs by deploying chat bots to run the sales funnel, deliver customer service and generate marketing and communications activities.
Conversational AI models disrupted business models more than 30 years ago, allowing companies to scale the delivery of basic customer service. Chatbots can answer simple customer queries 24 x 7 and as they have improved in their capabilities, they are fast becoming a preferred first point of contact.
Customers who now call a call centre or go into a store or branch are the customers that either don’t know what they should ask a chatbot, need advice or have a complicated issue to be resolved. Customer service operatives in the call centre are now the escalation experts and AI is the frontline.
The latest generation of conversational AI is generative, unlike traditional chatbots it creates original combinations of text as opposed to retrieving a consistent response to a question from a pre-defined programmed response.
While AI generative content is remarkable in its human like qualities, right now, customer service jobs are fairly safe.
- Generative Chatbots can make mistakes; in customer service you want to give your customers consistent and accurate answers, not creative ones. It is better to provide no response or to escalate a customer to a real person than to create a response that is potentially problematic for the business.
- Generative Chatbots can’t give advice (especially financial advice) or discuss life goals and options; you don’t want AI telling a customer to do something that will negatively impact their financial position. We know from previous research that consumers place a lot of trust in what technology tells them to do because it generally looks and sounds accurate. Hence businesses need to consider their liabilities in terms of what generative AI could instruct customers to do.
- Chatbots can’t help customers who ask incorrect questions or identify what the customer has misunderstood about a product or service. If customers are asking incorrect questions the AI will respond regardless, whereas a customer service agent can interrogate the customer to ensure their information and questions are accurate.
AI is a fast-evolving sector and there are already many ‘out of the box’ solutions being sold and utilised by businesses which range in quality and sophistication, but no AI model can currently replicate the intelligence and reasoning of a human customer service operative.
While AI disrupted customer service decades ago it is now about to disrupt the more creative knowledge-based internal functions of businesses and industry sectors. And like customer service, generative AI will likely replace the simple creative functions that could benefit from speed of response, including:
- Summarising disparate information into simple a narrative
- Generating basic code to complete specific tasks
- Generation of creative outputs that fit a desired tone and call to action.
These capabilities have not been widely accessible at speed and low cost until now. But like the early chatbots of the 1990s there will be teething problems.
There are key issues that businesses need to be aware of when considering AI for more creative tasks such as generating marketing communications.
Generative AI can perpetuate discrimination and even amplify prejudices if it is created and trained on data that does not reflect or represent the broader community.
This happens when there is a lack of diversity in the training dataset, insufficient data, misrepresentation in the data, or a failure to account for biases. Businesses that utilise third-party training datasets are especially vulnerable to these issues.
Generative AI never doubts itself and is not guided by caution when generating ideas. That little nagging feeling in the back of your mind often prevents people from taking a risk that could backfire and harm the reputation of the company. There have been many examples of companies that have suffered reputational damage from poor advertising creative or poorly chosen comments on social media.
For this reason, many AI generated creative ideas and responses will still require oversight by a human and won’t be automated the same way current chatbots can respond autonomously to service requests. Generative AI can create many ideas in a short timeframe which will need to be reviewed and refined.
To generate an original piece of creative that talks to a human truth will require working with the AI to inform and iterate the ideas. While ideas can be created quickly, unlike a traditional creative process it will lack the diversity of experience that a team of creative people can bring and is unlikely to create a completely original piece of content.
Generative AI currently creates originally structured output based on scouring a database of information. While it can transform that information it cannot generate new content that does not already exist.
While the latest generation of AI enables organisations to absorb, interpret and generate creative ideas quickly using significant volumes of data, ultimately the outcomes are still based on the data and parameters set by humans and lack human oversight that minimises risk of reputational damage.
If AI is the new creative frontline then like customer service operatives, creatives need to ensure they bring the high level expertise that can work with the generative outputs to deliver truly impactful and differentiated ideas that drive sales and strengthen brand reputation.
Fifth Dimension’s Trust Model
Fifth Dimension’s trust model centres on the premise that trust in brands has its foundations laid in two traits – the capability of the brand to do what it promises and the character of the brand to operate in an honest and ethical manner.
Fail on both trust traits and brands risk losing a customer they have let down for life and weakening brand growth due to the legacy of a proven poor reputation.
About Fifth Dimension Consulting
Fifth Dimension has been recognised for its groundbreaking work receiving multiple awards including: three prestigious 2021 FORSTA AIR (Achievement in Insight and Research) Awards including Judges Choice, a 2021 Confirmit ACE (Achievement in Customer Excellence) Award in the Innovation category, and a 2020 Confirmit AIR Insight and Research Award. In addition, Fifth Dimension was included in the highly respected 2020 GreenBook Research Industry Trends (GRIT) Top 25 Strategic Consultancies, as one of the world’s most innovative companies to make the list. Since its launch in 2006, Fifth Dimension’s four pillars of expertise have continued to evolve new capabilities to embrace uncertainty and drive the development of market leading approaches: strategy, experience, research and technology.