The future of conversational AI is not an AI takeover. Afterall, everything artificial is in fact human made. Intelligent businesses will leverage conversational AI that is controlled by HI (human intelligence). With humans in control, conversational AI delivers much better business outcomes. These include: more sales, rich personalised experiences and improved efficiencies. Businesses and consumers can only trust the AI and by extension a brand/company if they trust the humans providing it.

Despite the scaremongering, calls for development pauses and doomsday job annihilation pronouncements AI is not going anywhere.  If anything it will become more prolific. How businesses manage this, and take advantage of the technology, will depend on who they engage with to help them navigate their AI journey and to build and deliver their AI solutions.

Generative AI and Large Language Models (LLMs)

When it comes to generative AI and LLMs, there is a need to be aware of the well documented flaws (e.g hallucinations) associated with using LLMs. However, when they are accounted for as part of the workflow process within an entire conversational AI solution it is easy to mitigate the risks. Easy, that is, if you are engaging with conversational AI experts.

With the knowledge and acceptance that AI technology out of the box is not perfect, businesses can move forward with confidence. By taking measures such as adopting best practice and having embedded safeguards when deploying AI technology within their business operations. AI that delivers value and excludes the ability to damage must be the priority.

Trust in the AI

The predicament facing businesses today is how they can build trust in AI when there is so much mistrust. Mistrust that stems from the malicious actors operating without oversight.

First and foremost, organisations should forget about do-it-yourself conversational AI solutions if they want to leverage AI to address real business challenges and create real business value. Real value is realised when AI technology is connected and integrated into the entire conversational AI ecosystem. Only then can the right solution for a business be correctly architected.

Control

Partnering with conversational AI experts who offer control of the AI with platform, as well as flexibility that can leverage the most appropriate LLM for each use case, will serve businesses best. Control over the AI, combined with controls built into the conversational AI platform, ensures that customers and employees can be confident in the integrity, honesty and accuracy of every brand engagement. This is the foundation of trust.

Flexibility and Choice

The second critical factor that organisations should consider when implementing conversational AI solutions is flexibility and choice. The continually increasing number of LLMs becoming available is giving businesses the choice they need. Businesses shouldn’t feel overwhelmed by the choice available or let it be an obstacle to decision making.

Businesses do not need to lock themselves into a particular LLM if they partner with the right partner. That is, a partner that can offer a flexible platform that natively integrates seamlessly with all LLMs. Having the widest choice of LLMs available, gives businesses the advantage of being able to leverage specifically built LLMs for verticals and/or particular use cases. This enables richer personalisation, more sophisticated conversations and greater accuracy than has even been possible previously.

Conversational AI providers

Only by working with a provider who can offer  “click and lift” functionality, so businesses can use whichever LLM they want to, with different LLMs used for different use cases, will the real value of conversational AI be realised.

LLMs and AI prevalence

If we rewind just 12 months, AI wasn’t at the forefront of mainstream conversations. The mass attention directed towards LLMs began when the world became aware of OpenAI and GPT, notably ChatGPT at the back end of 2022.

Since then, GPT version 3.5 has evolved to GPT 4.0 and we have many other LLMs that have hit the market, such as PaLM 2, Claude, Cohere, Falcon, LLaMA, Guanaco, Vicuna, MPT-30B, and they are also hitting headlines, attracting attention and being tested by businesses. The big guns in the industry, the likes of Microsoft, Google, AWS and numerous others, are all investing heavily in LLM development and in AI. The AI race is on.

Looking at the market predictions put forward by the analyst community, it is evident that AI is big business:

• Valuates Reports says that: “The LLM market was valued at 10.5 Billion USD in 2022 and is anticipated to reach 40.8 Billion USD by 2029, witnessing a CAGR of 21.4% during the forecast period 2023-2029”
• Markets and Research reports that “The generative AI market is projected to grow from USD 11.3 billion in 2023 to USD 51.8 billion by 2028, at a compound annual growth rate (CAGR) of 35.6% during the forecast period.”
• QYResearch is projecting that “Global Large Language Model (LLM) market size in terms of revenue to reach 259,886.45 Million USD by 2029 from 1,302.93 Million USD in 2023, with a CAGR 141.72% during 2023-2029.”

The investment in AI and the expanding choice of LLMs available is definitely positive for businesses. Whilst trust, choice and flexibility are critical so too is the ability to leverage customised LLMs.

Realising the full potential of LLMs for business 

The guide-rails employed to control the LLMs need to be spelt out by the provider. These are inextricably linked to choice and flexibility, and sit at the core of performance, factual accuracy, reliability and also ensuring real value is realised from conversational AI implementations. The use of application specific datasets for specialised uses ensures the accuracy of results that general-purpose LLMs without the guide-rails are unable to deliver.

Looking at LLMs as a standalone technology will restrict their full potential. LLMs need to be seamlessly integrated and plugged into conversational AI solutions. LLMs must be customisable, manageable and controllable from a single platform that is built for the purpose and so fit for purpose.  They need to be customisable for specific applications as this will ensure they are more accessible and useful to every industry and more and more use cases.

It is easy for businesses to get carried away with the promises of AI and believe it is a simple off the shelf, out of the box technology that will work wonders. This is a false assumption. Businesses that do not engage with experts who understand not just the AI technology but importantly workflows, content and knowledge management and are able to provide solutions that consider the entire conversational AI ecosystem, will disappoint their customers, employees and shareholders.