What Exactly is this AI Thing? And What Does it Mean for the World of Proposals?
Artificial Intelligence (AI) is a hot topic in the proposal
field right now. In the last year or so, the Association of Proposal Management
Professionals (APMP) has hosted multiple webinars on AI at both the international and chapter levels. At Bid and Proposal Con
2019, there were even back-to-back sessions dedicated to the topic—and I was
honored to share some of my own insights as part of in Karthik Koutharapu’s
panel, “Leveraging AI for Persuasive Proposal Writing.”
From the audience and panelist reactions to the various
questions, it’s clear that many of us have some angst about the potential
negative effects on the industry. But some of us are more optimistic about the
ways AI may be able to improve our work-life balance. In this article, I provide
an overview of AI and present some of the ways I am hopeful that it will
improve our industry.
What is Artificial Intelligence
(AI)?
AI is the theory and development of computer systems able to
perform tasks that normally require human intelligence, such as visual
perception, speech recognition, decision-making, and translation between
languages. AI often revolves around the use of algorithms.
But what is an algorithm? An algorithm is a detailed,
step-by-step instruction set or formula for solving a problem or completing a
task. Algorithms are everywhere! A recipe for making food is an algorithm, the
process of folding a shirt or a pair of pants is an algorithm, and even the logical
reasoning you use when you play tic tac toe is an algorithm.
In computing, an algorithm is a set of instructions that a computer
can execute. Many AI algorithms are capable of learning from data. This branch
of AI—which is based on the idea that systems can learn from data, identify
patterns, and make decisions with minimal human intervention—is called machine
learning.
Machine learning algorithms can enhance themselves by
learning new heuristics (i.e., strategies, or "rules of thumb," that
have worked well in the past). Machine learning algorithms work on the basis
that strategies, algorithms, and inferences that worked well in the past are
likely to continue working well in the future. Simply put, machine learning
algorithms work by building a mathematical model based on some sample data, known
as "training data," to make future predictions or decisions.
How is AI Currently
Being Used in Proposals?
As demonstrated by the number of Bid and Proposal Con 2019
vendors already boasting AI capabilities, many companies are already leveraging
AI to automate and enhance the proposal development process. Currently, most of
these tools are focused on automating Question and Answer type proposals
(largely commercial applications) and language analysis (cross-cutting
applications). In the paragraphs to follow, I highlight four proposal tools that
leverage AI.
IBM’s Watson and Tone
Analyzer Application Programming Interfaces (APIs). As we learned from
Karthik at Bid and Proposal Con 2019, IBM uses the AI power of Watson and Tone
Analyzer APIs to develop more effective Executive Summaries. This proprietary tool
uses linguistic analysis to detect and score three types of tone from the
proposal content: emotion, social tendencies, and language style. This tool
allows users to upload content to quickly analyze and revise the language for
improved client impact.
VisibleThread. VisibleThread offers language analytics and AI solutions that are used by 7 of the top 10 U.S.
Government contractors. Companies use VisibleThread to increase efficiency, quality
check proposals, and drive more compliant content. Some of the most useful
features of VisibleThread include: compliance gap analysis, readability and
single tone of voice analysis, theme discovery and analysis, and concept
tracking.
reDock. reDock uses AI
and machine learning to automate content and data search tasks. The tool
enables users to find quickly and easily the most suitable information across
all of a company’s data repositories and software systems. This search engine filters
through existing documents to find profiles, corporate references, past
answers, and/or relevant approaches and presents the right section of
information, rather than the entire document. This eliminates the
time-consuming effort of sifting through hundreds of pages of proposal text for
the right content.
RFPIO. RFPIO offers an
intelligent answer library and auto-responses powered by AI. With RFPIO, a
company maintains their content in a repository called the Answer Library. When
a user searches for the right content or contributors for a project, the tool
makes a recommendation based on previous activity.
What are Some of the
Challenges with AI and Propsals?
Although AI tools are beginning to enhance our capabilities,
to be more effective, AI must become a more seamless part of our established
processes. Currently, the available AI tools are not particularly flexible, and
they don’t integrate well with our existing tools and workflows. Additionally, as
AI tools evolve, our companies will need to be prepared to provide the legwork
necessary to enable these tools to access accurate training data.
Not Seamlessly
Integrated. Currently, most of the common AI language analysis tools
require an extra step to perform the desired tasks. The existing proposal process
must be stopped, documents must be uploaded, and then the desired analyses can
be performed. This is because most of these tools are not integrated into each
company’s existing proposal management and version control tools (e.g., Privia,
SharePoint, Virtual Proposal Center (VPC)). To be more user friendly, and to
increase the usefulness, these tools need to be better integrated into the
existing tools being used for proposal development so that the analyses and
added functionality are seamless.
AI Requires Accurate
Training Data. This challenge is multi-part. First, the AI tools will need
access to the company’s data, so this will require integration effort on the
part of IT staff. And the more historical data the company has, the more time
and effort this is likely to take. Next, the AI tools need to understand how
effective the previous content was. If companies use their customer
relationship management (CRM) tools effectively to maintain accurate records of
proposal content, customer debriefs, and any resulting contracts—then this step
may not be too difficult. However, if companies store this information in
disparate places using tools that don’t communicate well, this task will become
more complex, difficult, and time consuming. Finally, to make sure that the AI
continues to learn and predict effectively, companies will need to make sure
the data remains up-to-date moving forward.
What is the Future
for AI in Proposals?
Although AI has already started to impact existing proposal
processes, we have really only begun to scratch the surface of its true
potential in the field. Because of its unemotional capabilities to make
predictions, AI has huge potential in supporting bid/no-bid decision so
companies can more effectively target the opportunities with the highest probabilities
of win. In addition, with its capability to quickly analyze massive amounts of
data to make predictions and decisions, AI can likely help improve price
analysis, price-to-win, and price development processes. Further, AI seems to
have huge potential to support the selection of proposed products and solutions.
Will AI eventually replace all of us and independently write
the proposals for our companies? I think most of us agree that this will never
happen in our lifetimes. However, I do believe that AI tools of our future will
ultimately empower our proposal teams. But to be more effective, AI must become
a seamless part of our established processes—it must be flexible and integrate
with our existing tools and workflows. We are not there yet, but we are getting
there. Leveraging AI effectively in the future, I believe we will increase the
efficiency of our overall proposal process by focusing on the right opportunities,
at the right time, with the right strategies.
Written by Ashley Kayes, CP APMP
Senior Proposal Consultant, AOC Key Solutions, Inc. (KSI)
https://www.linkedin.com/in/ashley-kayes-cp-apmp-a3750413/
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